Cure Model Regression
cureit.RdCure Model Regression
Usage
# S3 method for formula
cureit(
surv_formula,
cure_formula,
data,
conf.level = 0.95,
nboot = 100,
eps = 1e-07,
...
)
cureit(object, ...)
# S3 method for default
cureit(object, ...)Arguments
- surv_formula
formula with
Surv()on LHS and covariates on RHS.- cure_formula
formula with covariates for cure fraction on RHS
- data
data frame
- conf.level
confidence level. Default is 0.95.
- nboot
number of bootstrap samples used for inference.
- eps
convergence criterion for the EM algorithm.
- ...
passed to methods
- object
input object
See also
Other cureit() functions:
Brier_inference_bootstrap(),
broom_methods_cureit,
nomogram(),
predict.cureit()
Examples
cureit(surv_formula = Surv(ttdeath, death) ~ age + grade,
cure_formula = ~ age + grade, data = trial)
#> 0 were not able to fit
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002616112 0.569504769 0.345883977
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.575003030 0.009813492 0.108542405
#> grade_iii, Cure model
#> 0.823899189
#>
#> $surv_formula
#> Surv(ttdeath, death) ~ age + grade
#> <environment: 0x55a86496d8d8>
#>
#> $cure_formula
#> ~age + grade
#> <environment: 0x55a86496d8d8>
#>
#> $data
#> # A tibble: 200 × 8
#> trt age marker stage grade response death ttdeath
#> <chr> <dbl> <dbl> <fct> <fct> <int> <dbl> <dbl>
#> 1 Drug A 23 0.16 T1 II 0 0 24
#> 2 Drug B 9 1.11 T2 I 1 0 24
#> 3 Drug A 31 0.277 T1 II 0 0 24
#> 4 Drug A NA 2.07 T3 III 1 1 17.6
#> 5 Drug A 51 2.77 T4 III 1 1 16.4
#> 6 Drug B 39 0.613 T4 I 0 1 15.6
#> 7 Drug A 37 0.354 T1 II 0 0 24
#> 8 Drug A 32 1.74 T1 I 0 1 18.4
#> 9 Drug A 31 0.144 T1 II 0 0 24
#> 10 Drug B 34 0.205 T3 I 0 1 10.5
#> # ℹ 190 more rows
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> $surv_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $cure_xlevels
#> $cure_xlevels$grade
#> [1] "I" "II" "III"
#>
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure mod… -0.575 0.541 -1.06 -1.64 0.486 0.288
#> 2 age, Cure model 0.00981 0.0104 0.943 -0.0106 0.0302 0.346
#> 3 grade_ii, Cure model 0.109 0.323 0.336 -0.525 0.742 0.737
#> 4 grade_iii, Cure model 0.824 0.355 2.32 0.127 1.52 0.0204
#>
#> $tidy$df_surv
#> # A tibble: 3 × 7
#> term estimate std.error statistic conf.low conf.high p.value
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00262 0.00903 -0.290 -0.0203 0.0151 0.772
#> 2 grade_ii, Survival mo… 0.570 0.264 2.15 0.0513 1.09 0.0312
#> 3 grade_iii, Survival m… 0.346 0.238 1.45 -0.121 0.813 0.147
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003 0.009813 0.108542 0.823899
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.575003030 0.009813492 0.108542405 0.823899189
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002616112 0.569504769 0.345883977
#>
#> $b_var
#> [1] 0.2929483858 0.0001082733 0.1044469165 0.1262796115
#>
#> $b_sd
#> [1] 0.54124707 0.01040544 0.32318248 0.35535843
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.0623670 0.9431113 0.3358549 2.3185019
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.28806910 0.34562398 0.73698032 0.02042206
#>
#> $beta_var
#> [1] 8.154481e-05 6.990491e-02 5.679819e-02
#>
#> $beta_sd
#> [1] 0.009030216 0.264395373 0.238323701
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.2897064 2.1539892 1.4513201
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.77204083 0.03124102 0.14669075
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.000000000 0.000000000 0.000000000 0.604678067 0.658063410 0.000000000
#> [7] 0.417229340 0.000000000 0.879376354 0.000000000 0.000000000 0.744886187
#> [13] 0.787600867 0.142672058 0.944518547 0.000000000 0.693100768 0.000000000
#> [19] 0.000000000 0.000000000 0.000000000 0.540871173 0.006912639 0.976381134
#> [25] 0.640373656 0.000000000 0.000000000 0.684419417 0.522291631 0.000000000
#> [31] 0.278243702 0.000000000 0.000000000 0.000000000 0.246976530 0.821307758
#> [37] 0.000000000 0.666890646 0.466018936 0.456394953 0.829660071 0.854634203
#> [43] 0.000000000 0.531599829 0.000000000 0.000000000 0.000000000 0.846335953
#> [49] 0.446649365 0.887603756 0.000000000 0.000000000 0.368370905 0.837991986
#> [55] 0.736284601 0.368370905 0.762052697 0.904005497 0.000000000 0.130947018
#> [61] 0.000000000 0.000000000 0.178167087 0.000000000 0.298558895 0.093531067
#> [67] 0.960518552 0.000000000 0.000000000 0.000000000 0.000000000 0.387858887
#> [73] 0.968455884 0.020860827 0.613665875 0.000000000 0.753465281 0.000000000
#> [79] 0.000000000 0.000000000 0.586773524 0.036370054 0.000000000 0.427038837
#> [85] 0.267747949 0.984266892 0.106209363 0.895813391 0.000000000 0.000000000
#> [91] 0.727657186 0.397671772 0.000000000 0.246976530 0.631469660 0.920311545
#> [97] 0.000000000 0.000000000 0.000000000 0.348502061 0.550166021 0.862915985
#> [103] 0.436874482 0.000000000 0.494318881 0.513013956 0.000000000 0.118522726
#> [109] 0.000000000 0.503694197 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.779118376 0.649247645 0.000000000 0.992139734 0.308649170
#> [121] 0.080274841 0.568542449 0.000000000 0.000000000 0.718999352 0.475516896
#> [127] 0.000000000 0.201867710 0.000000000 0.000000000 0.224987874 0.796088245
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.912176411 0.000000000
#> [139] 0.000000000 0.000000000 0.952539418 0.318644852 0.000000000 0.000000000
#> [145] 0.236117909 0.804529313 0.770582430 0.000000000 0.701722215 0.328677697
#> [151] 0.871155498 0.000000000 0.000000000 0.000000000 0.000000000 0.065734870
#> [157] 0.000000000 0.338572747 0.675684959 0.050684149 0.154512416 0.358472658
#> [163] 0.559374570 0.000000000 0.000000000 0.000000000 0.189977968 0.000000000
#> [169] 0.812910823 0.000000000 0.407438340 0.710355937 0.577676416 0.000000000
#> [175] 0.936485829 0.484909262 0.000000000 0.000000000 0.928419678 0.622583868
#> [181] 0.288505592 0.000000000 0.586773524 0.000000000 0.166456957 0.000000000
#> [187] 0.213576414 0.000000000 0.000000000
#>
#> $Time
#> 1 2 3 5 6 7 8 9 10 11 12 13 14
#> 24.00 24.00 24.00 16.43 15.64 24.00 18.43 24.00 10.53 24.00 24.00 14.34 12.89
#> 15 16 17 18 19 20 21 22 23 24 25 26 27
#> 22.68 8.71 24.00 15.21 24.00 24.00 24.00 24.00 16.92 23.89 6.32 15.77 24.00
#> 28 29 30 31 32 33 34 35 36 37 38 39 40
#> 24.00 15.45 17.43 24.00 20.90 24.00 24.00 24.00 21.19 12.52 24.00 15.59 18.00
#> 41 42 43 44 45 46 47 48 49 51 52 53 54
#> 18.02 12.43 12.10 24.00 17.42 24.00 24.00 24.00 12.19 18.23 10.42 24.00 24.00
#> 55 56 57 58 60 61 62 63 64 65 66 67 68
#> 19.34 12.21 14.46 19.34 13.15 10.12 24.00 22.77 24.00 24.00 22.13 24.00 20.62
#> 69 70 71 72 74 75 76 77 78 79 80 81 82
#> 23.23 7.38 24.00 24.00 24.00 24.00 19.22 7.27 23.88 16.23 24.00 14.06 24.00
#> 83 84 85 86 87 88 90 91 92 93 94 95 96
#> 24.00 24.00 16.44 23.81 24.00 18.37 20.94 5.33 22.92 10.33 24.00 24.00 14.54
#> 97 98 99 100 101 102 103 104 105 106 107 108 109
#> 19.14 24.00 21.19 16.07 9.97 24.00 24.00 24.00 19.75 16.67 11.18 18.29 24.00
#> 110 111 112 113 116 117 118 119 120 121 122 123 125
#> 17.56 17.45 24.00 22.86 24.00 17.46 24.00 24.00 24.00 24.00 24.00 13.00 15.65
#> 126 127 128 129 130 131 132 133 134 135 136 137 138
#> 24.00 3.53 20.35 23.41 16.47 24.00 24.00 14.65 17.81 24.00 21.83 24.00 24.00
#> 139 140 141 142 143 144 145 146 147 148 149 150 151
#> 21.49 12.68 24.00 24.00 24.00 24.00 10.07 24.00 24.00 24.00 8.37 20.33 24.00
#> 152 153 154 155 156 157 158 159 160 161 162 163 164
#> 24.00 21.33 12.63 13.08 24.00 15.10 20.14 10.55 24.00 24.00 24.00 24.00 23.60
#> 165 166 167 168 169 170 171 172 173 174 175 176 177
#> 24.00 19.98 15.55 23.72 22.41 19.54 16.57 24.00 24.00 24.00 21.91 24.00 12.53
#> 178 179 180 181 182 183 184 185 186 187 188 190 191
#> 24.00 18.63 14.82 16.46 24.00 9.24 17.77 24.00 24.00 9.92 16.16 20.81 24.00
#> 192 193 194 196 197 198 200
#> 16.44 24.00 22.40 24.00 21.60 24.00 24.00
#>
#> $bootstrap_fit
#> $bootstrap_fit[[1]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001966861 0.350926729 0.160441258
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86805923 0.01757316 -0.23395094
#> grade_iii, Cure model
#> 1.17046064
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 86 23.81 1 58 0 1
#> 8 18.43 1 32 0 0
#> 179 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 16 8.71 1 71 0 1
#> 150 20.33 1 48 0 0
#> 194 22.40 1 38 0 1
#> 153 21.33 1 55 1 0
#> 158 20.14 1 74 1 0
#> 177 12.53 1 75 0 0
#> 30 17.43 1 78 0 0
#> 81 14.06 1 34 0 0
#> 105 19.75 1 60 0 0
#> 108 18.29 1 39 0 1
#> 96 14.54 1 33 0 1
#> 194.1 22.40 1 38 0 1
#> 36 21.19 1 48 0 1
#> 157 15.10 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 99 21.19 1 38 0 1
#> 167 15.55 1 56 1 0
#> 5.1 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 127 3.53 1 62 0 1
#> 14 12.89 1 21 0 0
#> 180 14.82 1 37 0 0
#> 123 13.00 1 44 1 0
#> 50 10.02 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 96.1 14.54 1 33 0 1
#> 15 22.68 1 48 0 0
#> 26.1 15.77 1 49 0 1
#> 55 19.34 1 69 0 1
#> 125 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 150.1 20.33 1 48 0 0
#> 85 16.44 1 36 0 0
#> 99.1 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 85.1 16.44 1 36 0 0
#> 69 23.23 1 25 0 1
#> 157.1 15.10 1 47 0 0
#> 49 12.19 1 48 1 0
#> 16.1 8.71 1 71 0 1
#> 99.2 21.19 1 38 0 1
#> 153.1 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 77 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 184 17.77 1 38 0 0
#> 16.2 8.71 1 71 0 1
#> 199 19.81 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 134 17.81 1 47 1 0
#> 41 18.02 1 40 1 0
#> 24 23.89 1 38 0 0
#> 113 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 52 10.42 1 52 0 1
#> 76 19.22 1 54 0 1
#> 16.3 8.71 1 71 0 1
#> 101 9.97 1 10 0 1
#> 114 13.68 1 NA 0 0
#> 107 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 96.2 14.54 1 33 0 1
#> 51 18.23 1 83 0 1
#> 153.2 21.33 1 55 1 0
#> 85.2 16.44 1 36 0 0
#> 110 17.56 1 65 0 1
#> 81.1 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 86.1 23.81 1 58 0 1
#> 164 23.60 1 76 0 1
#> 6 15.64 1 39 0 0
#> 8.1 18.43 1 32 0 0
#> 114.1 13.68 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 24.1 23.89 1 38 0 0
#> 14.1 12.89 1 21 0 0
#> 187 9.92 1 39 1 0
#> 5.2 16.43 1 51 0 1
#> 187.1 9.92 1 39 1 0
#> 78 23.88 1 43 0 0
#> 93.1 10.33 1 52 0 1
#> 159.1 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 155 13.08 1 26 0 0
#> 37 12.52 1 57 1 0
#> 56 12.21 1 60 0 0
#> 37.1 12.52 1 57 1 0
#> 106.1 16.67 1 49 1 0
#> 60.1 13.15 1 38 1 0
#> 88 18.37 1 47 0 0
#> 134.1 17.81 1 47 1 0
#> 61 10.12 1 36 0 1
#> 180.1 14.82 1 37 0 0
#> 55.1 19.34 1 69 0 1
#> 184.2 17.77 1 38 0 0
#> 52.1 10.42 1 52 0 1
#> 42 12.43 1 49 0 1
#> 36.1 21.19 1 48 0 1
#> 167.1 15.55 1 56 1 0
#> 199.1 19.81 1 NA 0 1
#> 5.3 16.43 1 51 0 1
#> 79 16.23 1 54 1 0
#> 125.1 15.65 1 67 1 0
#> 85.3 16.44 1 36 0 0
#> 110.1 17.56 1 65 0 1
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 27 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 143 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 147 24.00 0 76 1 0
#> 193 24.00 0 45 0 1
#> 122 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 162.1 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 53 24.00 0 32 0 1
#> 152.1 24.00 0 36 0 1
#> 53.1 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 33 24.00 0 53 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 73 24.00 0 NA 0 1
#> 118 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 151 24.00 0 42 0 0
#> 87 24.00 0 27 0 0
#> 109 24.00 0 48 0 0
#> 115 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 75 24.00 0 21 1 0
#> 138 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 109.1 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 144 24.00 0 28 0 1
#> 193.2 24.00 0 45 0 1
#> 132 24.00 0 55 0 0
#> 163 24.00 0 66 0 0
#> 161.2 24.00 0 45 0 0
#> 143.1 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 142 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 174.1 24.00 0 49 1 0
#> 144.1 24.00 0 28 0 1
#> 1 24.00 0 23 1 0
#> 48 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 161.3 24.00 0 45 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 147.1 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 156.2 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 174.2 24.00 0 49 1 0
#> 75.1 24.00 0 21 1 0
#> 172.1 24.00 0 41 0 0
#> 33.1 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 160.1 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 27.1 24.00 0 63 1 0
#> 186.1 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 35.1 24.00 0 51 0 0
#> 109.2 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 33.2 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 54.1 24.00 0 53 1 0
#> 27.2 24.00 0 63 1 0
#> 162.2 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.868 NA NA NA
#> 2 age, Cure model 0.0176 NA NA NA
#> 3 grade_ii, Cure model -0.234 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00197 NA NA NA
#> 2 grade_ii, Survival model 0.351 NA NA NA
#> 3 grade_iii, Survival model 0.160 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86806 0.01757 -0.23395 1.17046
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 246.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86805923 0.01757316 -0.23395094 1.17046064
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001966861 0.350926729 0.160441258
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.07355755 0.39219405 0.38253466 0.58114101 0.95693335 0.29314200
#> [7] 0.17440784 0.19974076 0.31362528 0.82228720 0.51183220 0.75215040
#> [13] 0.32382219 0.42081634 0.72861949 0.17440784 0.23296980 0.69678582
#> [19] 0.82228720 0.23296980 0.66448702 0.58114101 0.68875678 0.99279556
#> [25] 0.79908142 0.71271606 0.79129968 0.62308456 0.72861949 0.16070000
#> [31] 0.62308456 0.33397907 0.63978775 0.81455648 0.29314200 0.54708925
#> [37] 0.23296980 0.91281978 0.11870331 0.54708925 0.13296287 0.69678582
#> [43] 0.86800906 0.95693335 0.23296980 0.19974076 0.52078067 0.98557402
#> [49] 0.28264126 0.46727600 0.95693335 0.37285423 0.44917716 0.43982229
#> [55] 0.02136538 0.14687619 0.88308816 0.46727600 0.89799094 0.35357973
#> [61] 0.95693335 0.93496924 0.87556742 0.76789780 0.72861949 0.43035941
#> [67] 0.19974076 0.54708925 0.49404062 0.75215040 0.52970958 0.07355755
#> [73] 0.10338693 0.65622472 0.39219405 0.68067459 0.02136538 0.79908142
#> [79] 0.94235035 0.58114101 0.94235035 0.05404169 0.91281978 0.88308816
#> [85] 0.35357973 0.78347571 0.83763032 0.86041359 0.83763032 0.52970958
#> [91] 0.76789780 0.41121501 0.44917716 0.92757660 0.71271606 0.33397907
#> [97] 0.46727600 0.89799094 0.85280972 0.23296980 0.66448702 0.58114101
#> [103] 0.61460927 0.63978775 0.54708925 0.49404062 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 86 8 179 5 16 150 194 153 158 177 30 81 105
#> 23.81 18.43 18.63 16.43 8.71 20.33 22.40 21.33 20.14 12.53 17.43 14.06 19.75
#> 108 96 194.1 36 157 177.1 99 167 5.1 18 127 14 180
#> 18.29 14.54 22.40 21.19 15.10 12.53 21.19 15.55 16.43 15.21 3.53 12.89 14.82
#> 123 26 96.1 15 26.1 55 125 140 150.1 85 99.1 93 129
#> 13.00 15.77 14.54 22.68 15.77 19.34 15.65 12.68 20.33 16.44 21.19 10.33 23.41
#> 85.1 69 157.1 49 16.1 99.2 153.1 23 77 190 184 16.2 97
#> 16.44 23.23 15.10 12.19 8.71 21.19 21.33 16.92 7.27 20.81 17.77 8.71 19.14
#> 134 41 24 113 159 184.1 52 76 16.3 101 107 60 96.2
#> 17.81 18.02 23.89 22.86 10.55 17.77 10.42 19.22 8.71 9.97 11.18 13.15 14.54
#> 51 153.2 85.2 110 81.1 106 86.1 164 6 8.1 29 24.1 14.1
#> 18.23 21.33 16.44 17.56 14.06 16.67 23.81 23.60 15.64 18.43 15.45 23.89 12.89
#> 187 5.2 187.1 78 93.1 159.1 76.1 155 37 56 37.1 106.1 60.1
#> 9.92 16.43 9.92 23.88 10.33 10.55 19.22 13.08 12.52 12.21 12.52 16.67 13.15
#> 88 134.1 61 180.1 55.1 184.2 52.1 42 36.1 167.1 5.3 79 125.1
#> 18.37 17.81 10.12 14.82 19.34 17.77 10.42 12.43 21.19 15.55 16.43 16.23 15.65
#> 85.3 110.1 9 152 27 156 156.1 34 143 20 147 193 122
#> 16.44 17.56 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 162.1 54 53 152.1 53.1 119 33 161 161.1 118 193.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 109 196 148 174 116 72 112 75 138 160 178 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 102 144 193.2 132 163 161.2 143.1 64 121 142 28 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 1 48 47 141 80 22 163.1 161.3 65 65.1 147.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 186 174.2 75.1 172.1 33.1 142.1 104 160.1 9.1 27.1 186.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 35.1 109.2 84 33.2 131 54.1 27.2 162.2 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[2]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.02078333 0.40725440 0.68483264
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.091623453 0.004763515 -0.051357836
#> grade_iii, Cure model
#> 0.189731683
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 171 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 78 23.88 1 43 0 0
#> 150 20.33 1 48 0 0
#> 32 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 40 18.00 1 28 1 0
#> 199 19.81 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 177 12.53 1 75 0 0
#> 78.1 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 145 10.07 1 65 1 0
#> 167 15.55 1 56 1 0
#> 129 23.41 1 53 1 0
#> 114 13.68 1 NA 0 0
#> 55 19.34 1 69 0 1
#> 51 18.23 1 83 0 1
#> 43 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 23 16.92 1 61 0 0
#> 5 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 175 21.91 1 43 0 0
#> 130 16.47 1 53 0 1
#> 197 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 68 20.62 1 44 0 0
#> 89 11.44 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 169 22.41 1 46 0 0
#> 40.1 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 136 21.83 1 43 0 1
#> 66 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 153 21.33 1 55 1 0
#> 56 12.21 1 60 0 0
#> 25 6.32 1 34 1 0
#> 60 13.15 1 38 1 0
#> 78.2 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 78.3 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 8 18.43 1 32 0 0
#> 177.1 12.53 1 75 0 0
#> 169.1 22.41 1 46 0 0
#> 89.1 11.44 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 5.1 16.43 1 51 0 1
#> 24 23.89 1 38 0 0
#> 155.1 13.08 1 26 0 0
#> 92 22.92 1 47 0 1
#> 24.1 23.89 1 38 0 0
#> 23.1 16.92 1 61 0 0
#> 100.1 16.07 1 60 0 0
#> 183 9.24 1 67 1 0
#> 99.1 21.19 1 38 0 1
#> 114.1 13.68 1 NA 0 0
#> 40.2 18.00 1 28 1 0
#> 100.2 16.07 1 60 0 0
#> 179 18.63 1 42 0 0
#> 188.1 16.16 1 46 0 1
#> 181 16.46 1 45 0 1
#> 197.1 21.60 1 69 1 0
#> 81.1 14.06 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 24.2 23.89 1 38 0 0
#> 130.1 16.47 1 53 0 1
#> 106 16.67 1 49 1 0
#> 158 20.14 1 74 1 0
#> 130.2 16.47 1 53 0 1
#> 91.1 5.33 1 61 0 1
#> 76 19.22 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 37.1 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 149 8.37 1 33 1 0
#> 14 12.89 1 21 0 0
#> 77.1 7.27 1 67 0 1
#> 30 17.43 1 78 0 0
#> 129.1 23.41 1 53 1 0
#> 58 19.34 1 39 0 0
#> 5.2 16.43 1 51 0 1
#> 78.4 23.88 1 43 0 0
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 30.1 17.43 1 78 0 0
#> 63.2 22.77 1 31 1 0
#> 181.1 16.46 1 45 0 1
#> 76.1 19.22 1 54 0 1
#> 13 14.34 1 54 0 1
#> 166 19.98 1 48 0 0
#> 194 22.40 1 38 0 1
#> 63.3 22.77 1 31 1 0
#> 69 23.23 1 25 0 1
#> 5.3 16.43 1 51 0 1
#> 76.2 19.22 1 54 0 1
#> 42.1 12.43 1 49 0 1
#> 177.2 12.53 1 75 0 0
#> 50 10.02 1 NA 1 0
#> 18 15.21 1 49 1 0
#> 74 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 22 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 95.1 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 156 24.00 0 50 1 0
#> 31 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 156.1 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 200.1 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 161 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 121.1 24.00 0 57 1 0
#> 165 24.00 0 47 0 0
#> 9.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 178.1 24.00 0 52 1 0
#> 72.1 24.00 0 40 0 1
#> 147 24.00 0 76 1 0
#> 82 24.00 0 34 0 0
#> 1 24.00 0 23 1 0
#> 143 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 17 24.00 0 38 0 1
#> 95.2 24.00 0 68 0 1
#> 142 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 126 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 82.1 24.00 0 34 0 0
#> 3 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 163 24.00 0 66 0 0
#> 1.1 24.00 0 23 1 0
#> 200.2 24.00 0 64 0 0
#> 11 24.00 0 42 0 1
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 163.1 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 126.1 24.00 0 48 0 0
#> 95.3 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 176 24.00 0 43 0 1
#> 11.1 24.00 0 42 0 1
#> 94 24.00 0 51 0 1
#> 121.2 24.00 0 57 1 0
#> 165.1 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 47.1 24.00 0 38 0 1
#> 31.1 24.00 0 36 0 1
#> 82.2 24.00 0 34 0 0
#> 151 24.00 0 42 0 0
#> 109.1 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 109.2 24.00 0 48 0 0
#> 109.3 24.00 0 48 0 0
#> 143.1 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 35 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 174 24.00 0 49 1 0
#> 146 24.00 0 63 1 0
#> 65 24.00 0 57 1 0
#> 3.1 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 198.2 24.00 0 66 0 1
#> 22.1 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0916 NA NA NA
#> 2 age, Cure model 0.00476 NA NA NA
#> 3 grade_ii, Cure model -0.0514 NA NA NA
#> 4 grade_iii, Cure model 0.190 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0208 NA NA NA
#> 2 grade_ii, Survival model 0.407 NA NA NA
#> 3 grade_iii, Survival model 0.685 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.091623 0.004764 -0.051358 0.189732
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 262.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.091623453 0.004763515 -0.051357836 0.189731683
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.02078333 0.40725440 0.68483264
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8637620 0.9046429 0.9954062 0.3649311 0.7457355 0.7251242 0.9259047
#> [8] 0.8122590 0.5701046 0.9317644 0.9545287 0.3649311 0.9858317 0.9783617
#> [15] 0.9199455 0.4759216 0.7649227 0.8074768 0.9758147 0.7321393 0.9138475
#> [22] 0.8983367 0.8519155 0.8853918 0.6683979 0.8676151 0.6872099 0.8351698
#> [29] 0.7389842 0.9882917 0.9517090 0.6270728 0.8122590 0.5426541 0.6780548
#> [36] 0.6585352 0.5426541 0.8023894 0.6157107 0.7031592 0.9732269 0.9930405
#> [43] 0.9375312 0.3649311 0.8478443 0.8307223 0.7108537 0.3649311 0.9626920
#> [50] 0.7972480 0.9545287 0.6270728 0.9432172 0.8853918 0.2317729 0.9432172
#> [57] 0.5279785 0.2317729 0.8519155 0.9046429 0.9808773 0.7108537 0.8122590
#> [64] 0.9046429 0.7920751 0.8983367 0.8784116 0.6872099 0.9317644 0.9375312
#> [71] 0.2317729 0.8676151 0.8598452 0.7523837 0.8676151 0.9954062 0.7765169
#> [78] 0.5701046 0.9626920 0.8261103 0.9833607 0.9488787 0.9882917 0.8395186
#> [85] 0.4759216 0.7649227 0.8853918 0.3649311 0.9680238 0.9169131 0.8395186
#> [92] 0.5701046 0.8784116 0.7765169 0.9288581 0.7586976 0.6483667 0.5701046
#> [99] 0.5113278 0.8853918 0.7765169 0.9680238 0.9545287 0.9229403 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000 0.0000000
#>
#> $Time
#> 171 100 91 78 150 32 180 40 63 81 177 78.1 70
#> 16.57 16.07 5.33 23.88 20.33 20.90 14.82 18.00 22.77 14.06 12.53 23.88 7.38
#> 145 167 129 55 51 43 190 6 188 23 5 175 130
#> 10.07 15.55 23.41 19.34 18.23 12.10 20.81 15.64 16.16 16.92 16.43 21.91 16.47
#> 197 111 68 77 154 169 40.1 113 136 66 113.1 88 15
#> 21.60 17.45 20.62 7.27 12.63 22.41 18.00 22.86 21.83 22.13 22.86 18.37 22.68
#> 153 56 25 60 78.2 45 110 99 78.3 37 8 177.1 169.1
#> 21.33 12.21 6.32 13.15 23.88 17.42 17.56 21.19 23.88 12.52 18.43 12.53 22.41
#> 155 5.1 24 155.1 92 24.1 23.1 100.1 183 99.1 40.2 100.2 179
#> 13.08 16.43 23.89 13.08 22.92 23.89 16.92 16.07 9.24 21.19 18.00 16.07 18.63
#> 188.1 181 197.1 81.1 60.1 24.2 130.1 106 158 130.2 91.1 76 63.1
#> 16.16 16.46 21.60 14.06 13.15 23.89 16.47 16.67 20.14 16.47 5.33 19.22 22.77
#> 37.1 184 149 14 77.1 30 129.1 58 5.2 78.4 42 39 30.1
#> 12.52 17.77 8.37 12.89 7.27 17.43 23.41 19.34 16.43 23.88 12.43 15.59 17.43
#> 63.2 181.1 76.1 13 166 194 63.3 69 5.3 76.2 42.1 177.2 18
#> 22.77 16.46 19.22 14.34 19.98 22.40 22.77 23.23 16.43 19.22 12.43 12.53 15.21
#> 74 72 185 193 9 46 200 22 80 95 95.1 156 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 156.1 121 200.1 53 161 104 178 83 121.1 165 9.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 72.1 147 82 1 143 2 17 95.2 142 12 126 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 3 122 163 1.1 200.2 11 34 120 64 163.1 84 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.3 47 83.1 144 176 11.1 94 121.2 165.1 198 109 47.1 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.2 151 109.1 12.1 109.2 109.3 143.1 182 35 75 174 146 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 198.1 138 196 118 80.1 152 198.2 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[3]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007331583 0.018914927 0.021213878
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88433706 0.01602315 0.08699840
#> grade_iii, Cure model
#> 0.96022712
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 125 15.65 1 67 1 0
#> 133 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 128 20.35 1 35 0 1
#> 100 16.07 1 60 0 0
#> 63 22.77 1 31 1 0
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 175.1 21.91 1 43 0 0
#> 14 12.89 1 21 0 0
#> 86 23.81 1 58 0 1
#> 57 14.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 91 5.33 1 61 0 1
#> 180 14.82 1 37 0 0
#> 63.1 22.77 1 31 1 0
#> 133.1 14.65 1 57 0 0
#> 59 10.16 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 117 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 97 19.14 1 65 0 1
#> 56 12.21 1 60 0 0
#> 58 19.34 1 39 0 0
#> 149 8.37 1 33 1 0
#> 130 16.47 1 53 0 1
#> 168 23.72 1 70 0 0
#> 41 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 194 22.40 1 38 0 1
#> 58.1 19.34 1 39 0 0
#> 45.1 17.42 1 54 0 1
#> 60 13.15 1 38 1 0
#> 4 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 187 9.92 1 39 1 0
#> 167 15.55 1 56 1 0
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 92 22.92 1 47 0 1
#> 60.1 13.15 1 38 1 0
#> 90 20.94 1 50 0 1
#> 127 3.53 1 62 0 1
#> 188 16.16 1 46 0 1
#> 61 10.12 1 36 0 1
#> 114 13.68 1 NA 0 0
#> 108 18.29 1 39 0 1
#> 99 21.19 1 38 0 1
#> 91.1 5.33 1 61 0 1
#> 26.1 15.77 1 49 0 1
#> 127.1 3.53 1 62 0 1
#> 158 20.14 1 74 1 0
#> 52 10.42 1 52 0 1
#> 96 14.54 1 33 0 1
#> 85 16.44 1 36 0 0
#> 86.1 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 13 14.34 1 54 0 1
#> 145 10.07 1 65 1 0
#> 157 15.10 1 47 0 0
#> 136 21.83 1 43 0 1
#> 106 16.67 1 49 1 0
#> 29 15.45 1 68 1 0
#> 129.1 23.41 1 53 1 0
#> 66 22.13 1 53 0 0
#> 8 18.43 1 32 0 0
#> 192 16.44 1 31 1 0
#> 36.1 21.19 1 48 0 1
#> 133.2 14.65 1 57 0 0
#> 139 21.49 1 63 1 0
#> 15.1 22.68 1 48 0 0
#> 194.1 22.40 1 38 0 1
#> 130.1 16.47 1 53 0 1
#> 77 7.27 1 67 0 1
#> 107 11.18 1 54 1 0
#> 92.1 22.92 1 47 0 1
#> 69 23.23 1 25 0 1
#> 170.1 19.54 1 43 0 1
#> 99.1 21.19 1 38 0 1
#> 181 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 181.1 16.46 1 45 0 1
#> 170.2 19.54 1 43 0 1
#> 170.3 19.54 1 43 0 1
#> 60.2 13.15 1 38 1 0
#> 4.1 17.64 1 NA 0 1
#> 169.1 22.41 1 46 0 0
#> 190.1 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 89 11.44 1 NA 0 0
#> 134 17.81 1 47 1 0
#> 181.2 16.46 1 45 0 1
#> 175.2 21.91 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 63.2 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 124 9.73 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 32 20.90 1 37 1 0
#> 6.1 15.64 1 39 0 0
#> 49 12.19 1 48 1 0
#> 157.1 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 129.2 23.41 1 53 1 0
#> 53 24.00 0 32 0 1
#> 160 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 46 24.00 0 71 0 0
#> 12 24.00 0 63 0 0
#> 103 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 11 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 84 24.00 0 39 0 1
#> 148 24.00 0 61 1 0
#> 172 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 22 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 162 24.00 0 51 0 0
#> 148.1 24.00 0 61 1 0
#> 53.1 24.00 0 32 0 1
#> 34 24.00 0 36 0 0
#> 109 24.00 0 48 0 0
#> 33 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 46.1 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 135 24.00 0 58 1 0
#> 73 24.00 0 NA 0 1
#> 82 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 53.2 24.00 0 32 0 1
#> 3.1 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 11.1 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 46.2 24.00 0 71 0 0
#> 3.2 24.00 0 31 1 0
#> 2.1 24.00 0 9 0 0
#> 161.1 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 191 24.00 0 60 0 1
#> 38 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 34.2 24.00 0 36 0 0
#> 126 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 165 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 103.1 24.00 0 56 1 0
#> 22.1 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 172.2 24.00 0 41 0 0
#> 119.1 24.00 0 17 0 0
#> 12.1 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 109.1 24.00 0 48 0 0
#> 196 24.00 0 19 0 0
#> 47.1 24.00 0 38 0 1
#> 198.1 24.00 0 66 0 1
#> 80 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 64 24.00 0 43 0 0
#> 156 24.00 0 50 1 0
#> 156.1 24.00 0 50 1 0
#> 35 24.00 0 51 0 0
#> 115 24.00 0 NA 1 0
#> 144.1 24.00 0 28 0 1
#> 9 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 11.2 24.00 0 42 0 1
#> 104 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 35.1 24.00 0 51 0 0
#> 64.1 24.00 0 43 0 0
#> 98.1 24.00 0 34 1 0
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.884 NA NA NA
#> 2 age, Cure model 0.0160 NA NA NA
#> 3 grade_ii, Cure model 0.0870 NA NA NA
#> 4 grade_iii, Cure model 0.960 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00733 NA NA NA
#> 2 grade_ii, Survival model 0.0189 NA NA NA
#> 3 grade_iii, Survival model 0.0212 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88434 0.01602 0.08700 0.96023
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 249.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88433706 0.01602315 0.08699840 0.96022712
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007331583 0.018914927 0.021213878
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.26656271 0.73752221 0.79754552 0.32310725 0.61049325 0.58520495
#> [7] 0.45240023 0.71443870 0.20648249 0.47130523 0.32310725 0.87654776
#> [13] 0.04686896 0.82657221 0.72221167 0.10948145 0.43342354 0.97341083
#> [19] 0.79012754 0.20648249 0.79754552 0.90476253 0.60204273 0.92561313
#> [25] 0.53328515 0.89071912 0.50662885 0.95987283 0.65155798 0.08887707
#> [31] 0.56802884 0.61885447 0.88365426 0.19290193 0.28954663 0.50662885
#> [37] 0.61885447 0.84818739 0.37543720 0.94624201 0.76026887 0.52440104
#> [43] 0.24275737 0.16618484 0.84818739 0.41382417 0.98675998 0.70661873
#> [49] 0.93251135 0.55936460 0.37543720 0.97341083 0.72221167 0.98675998
#> [55] 0.46192557 0.91868934 0.81928145 0.69099117 0.04686896 0.86943165
#> [61] 0.84098297 0.93939277 0.77531811 0.35438495 0.64342098 0.76781848
#> [67] 0.10948145 0.31191112 0.54207481 0.69099117 0.37543720 0.79754552
#> [73] 0.36500475 0.24275737 0.28954663 0.65155798 0.96665769 0.91173960
#> [79] 0.16618484 0.15113198 0.47130523 0.37543720 0.66752960 0.82657221
#> [85] 0.66752960 0.47130523 0.47130523 0.84818739 0.26656271 0.43342354
#> [91] 0.74516456 0.57664493 0.66752960 0.32310725 0.54207481 0.20648249
#> [97] 0.63523641 0.58520495 0.42366201 0.74516456 0.89775315 0.77531811
#> [103] 0.95307364 0.10948145 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 169 125 133 175 30 184 128 100 63 170 175.1 14 86
#> 22.41 15.65 14.65 21.91 17.43 17.77 20.35 16.07 22.77 19.54 21.91 12.89 23.81
#> 57 26 129 190 91 180 63.1 133.1 43 117 93 97 56
#> 14.46 15.77 23.41 20.81 5.33 14.82 22.77 14.65 12.10 17.46 10.33 19.14 12.21
#> 58 149 130 168 41 45 177 113 194 58.1 45.1 60 36
#> 19.34 8.37 16.47 23.72 18.02 17.42 12.53 22.86 22.40 19.34 17.42 13.15 21.19
#> 187 167 76 15 92 60.1 90 127 188 61 108 99 91.1
#> 9.92 15.55 19.22 22.68 22.92 13.15 20.94 3.53 16.16 10.12 18.29 21.19 5.33
#> 26.1 127.1 158 52 96 85 86.1 123 13 145 157 136 106
#> 15.77 3.53 20.14 10.42 14.54 16.44 23.81 13.00 14.34 10.07 15.10 21.83 16.67
#> 29 129.1 66 8 192 36.1 133.2 139 15.1 194.1 130.1 77 107
#> 15.45 23.41 22.13 18.43 16.44 21.19 14.65 21.49 22.68 22.40 16.47 7.27 11.18
#> 92.1 69 170.1 99.1 181 57.1 181.1 170.2 170.3 60.2 169.1 190.1 6
#> 22.92 23.23 19.54 21.19 16.46 14.46 16.46 19.54 19.54 13.15 22.41 20.81 15.64
#> 134 181.2 175.2 8.1 63.2 23 184.1 32 6.1 49 157.1 183 129.2
#> 17.81 16.46 21.91 18.43 22.77 16.92 17.77 20.90 15.64 12.19 15.10 9.24 23.41
#> 53 160 147 46 12 103 3 176 198 112 11 141 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 148 172 67 22 31 193 162 148.1 53.1 34 109 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 146 46.1 143 34.1 178 33.1 135 82 2 53.2 3.1 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 186 131 46.2 3.2 2.1 161.1 132 191 38 54 137 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 126 172.1 98 165 119 103.1 22.1 185 172.2 119.1 12.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 196 47.1 198.1 80 65 64 156 156.1 35 144.1 9 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.2 104 95 35.1 64.1 98.1 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[4]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009092689 0.744491058 0.565386031
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.47182023 0.02682031 -0.14422945
#> grade_iii, Cure model
#> 1.21435359
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 192 16.44 1 31 1 0
#> 57 14.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 23 16.92 1 61 0 0
#> 77 7.27 1 67 0 1
#> 25 6.32 1 34 1 0
#> 26.1 15.77 1 49 0 1
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 90 20.94 1 50 0 1
#> 108 18.29 1 39 0 1
#> 93 10.33 1 52 0 1
#> 179 18.63 1 42 0 0
#> 179.1 18.63 1 42 0 0
#> 13 14.34 1 54 0 1
#> 81 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 101 9.97 1 10 0 1
#> 78 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 32 20.90 1 37 1 0
#> 89 11.44 1 NA 0 0
#> 81.1 14.06 1 34 0 0
#> 133 14.65 1 57 0 0
#> 79 16.23 1 54 1 0
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 155 13.08 1 26 0 0
#> 113 22.86 1 34 0 0
#> 13.1 14.34 1 54 0 1
#> 130 16.47 1 53 0 1
#> 30 17.43 1 78 0 0
#> 130.1 16.47 1 53 0 1
#> 93.1 10.33 1 52 0 1
#> 8 18.43 1 32 0 0
#> 108.1 18.29 1 39 0 1
#> 8.1 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 99 21.19 1 38 0 1
#> 181 16.46 1 45 0 1
#> 111 17.45 1 47 0 1
#> 123 13.00 1 44 1 0
#> 168 23.72 1 70 0 0
#> 199 19.81 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 77.1 7.27 1 67 0 1
#> 59 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 155.1 13.08 1 26 0 0
#> 40 18.00 1 28 1 0
#> 125 15.65 1 67 1 0
#> 114 13.68 1 NA 0 0
#> 184.1 17.77 1 38 0 0
#> 168.1 23.72 1 70 0 0
#> 43 12.10 1 61 0 1
#> 24 23.89 1 38 0 0
#> 85 16.44 1 36 0 0
#> 158.1 20.14 1 74 1 0
#> 76 19.22 1 54 0 1
#> 69 23.23 1 25 0 1
#> 5 16.43 1 51 0 1
#> 136 21.83 1 43 0 1
#> 77.2 7.27 1 67 0 1
#> 96 14.54 1 33 0 1
#> 76.1 19.22 1 54 0 1
#> 30.1 17.43 1 78 0 0
#> 32.1 20.90 1 37 1 0
#> 59.1 10.16 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 13.2 14.34 1 54 0 1
#> 108.2 18.29 1 39 0 1
#> 86 23.81 1 58 0 1
#> 189.1 10.51 1 NA 1 0
#> 111.1 17.45 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 133.1 14.65 1 57 0 0
#> 127.1 3.53 1 62 0 1
#> 188 16.16 1 46 0 1
#> 92 22.92 1 47 0 1
#> 51.2 18.23 1 83 0 1
#> 168.2 23.72 1 70 0 0
#> 155.2 13.08 1 26 0 0
#> 105 19.75 1 60 0 0
#> 197 21.60 1 69 1 0
#> 66 22.13 1 53 0 0
#> 36 21.19 1 48 0 1
#> 150 20.33 1 48 0 0
#> 42 12.43 1 49 0 1
#> 125.1 15.65 1 67 1 0
#> 25.1 6.32 1 34 1 0
#> 66.1 22.13 1 53 0 0
#> 180 14.82 1 37 0 0
#> 189.2 10.51 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 155.3 13.08 1 26 0 0
#> 91 5.33 1 61 0 1
#> 188.1 16.16 1 46 0 1
#> 81.2 14.06 1 34 0 0
#> 107 11.18 1 54 1 0
#> 97.1 19.14 1 65 0 1
#> 45.2 17.42 1 54 0 1
#> 117 17.46 1 26 0 1
#> 175 21.91 1 43 0 0
#> 70 7.38 1 30 1 0
#> 128 20.35 1 35 0 1
#> 149 8.37 1 33 1 0
#> 93.2 10.33 1 52 0 1
#> 44 24.00 0 56 0 0
#> 122 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 162 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 34 24.00 0 36 0 0
#> 21.2 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 161 24.00 0 45 0 0
#> 151 24.00 0 42 0 0
#> 173 24.00 0 19 0 1
#> 12 24.00 0 63 0 0
#> 3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 102 24.00 0 49 0 0
#> 82 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 35 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 178 24.00 0 52 1 0
#> 102.1 24.00 0 49 0 0
#> 31 24.00 0 36 0 1
#> 142 24.00 0 53 0 0
#> 53.1 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 173.1 24.00 0 19 0 1
#> 82.1 24.00 0 34 0 0
#> 131 24.00 0 66 0 0
#> 82.2 24.00 0 34 0 0
#> 53.2 24.00 0 32 0 1
#> 122.1 24.00 0 66 0 0
#> 142.1 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 161.1 24.00 0 45 0 0
#> 46 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 83 24.00 0 6 0 0
#> 84 24.00 0 39 0 1
#> 2 24.00 0 9 0 0
#> 67 24.00 0 25 0 0
#> 191 24.00 0 60 0 1
#> 44.1 24.00 0 56 0 0
#> 83.1 24.00 0 6 0 0
#> 161.2 24.00 0 45 0 0
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 148.1 24.00 0 61 1 0
#> 98 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 7.1 24.00 0 37 1 0
#> 83.2 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 21.3 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 17 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 161.3 24.00 0 45 0 0
#> 138 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 11.1 24.00 0 42 0 1
#> 83.3 24.00 0 6 0 0
#> 174.1 24.00 0 49 1 0
#> 174.2 24.00 0 49 1 0
#> 148.2 24.00 0 61 1 0
#> 20.1 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 138.1 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 80.1 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.47 NA NA NA
#> 2 age, Cure model 0.0268 NA NA NA
#> 3 grade_ii, Cure model -0.144 NA NA NA
#> 4 grade_iii, Cure model 1.21 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00909 NA NA NA
#> 2 grade_ii, Survival model 0.744 NA NA NA
#> 3 grade_iii, Survival model 0.565 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.47182 0.02682 -0.14423 1.21435
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 239.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.47182023 0.02682031 -0.14422945 1.21435359
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009092689 0.744491058 0.565386031
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.397158455 0.574912023 0.720745844 0.495698527 0.633616201 0.525111335
#> [7] 0.924299764 0.952774404 0.633616201 0.672173538 0.981128871 0.169292004
#> [13] 0.327815906 0.866422532 0.287427460 0.287427460 0.730483860 0.759222776
#> [19] 0.267834544 0.436402535 0.895386587 0.006915959 0.218915359 0.179828717
#> [25] 0.759222776 0.691518264 0.604396199 0.357248313 0.357248313 0.788254026
#> [31] 0.074787033 0.730483860 0.545195430 0.475799036 0.545195430 0.866422532
#> [37] 0.307454085 0.327815906 0.307454085 0.416645452 0.148729762 0.564967582
#> [43] 0.456313577 0.827122456 0.021519598 0.535186206 0.924299764 0.045468264
#> [49] 0.788254026 0.387106141 0.652936074 0.416645452 0.021519598 0.846797298
#> [55] 0.001683886 0.574912023 0.218915359 0.248278462 0.055780020 0.594525024
#> [61] 0.126696563 0.924299764 0.710985534 0.248278462 0.475799036 0.179828717
#> [67] 0.084516256 0.730483860 0.327815906 0.014242772 0.456313577 0.397158455
#> [73] 0.691518264 0.981128871 0.614221084 0.065384330 0.357248313 0.021519598
#> [79] 0.788254026 0.238238004 0.137767615 0.094644907 0.148729762 0.208964752
#> [85] 0.836967237 0.652936074 0.952774404 0.094644907 0.681826301 0.495698527
#> [91] 0.788254026 0.971647199 0.614221084 0.759222776 0.856626129 0.267834544
#> [97] 0.495698527 0.446401293 0.115438840 0.914721853 0.199179008 0.905083113
#> [103] 0.866422532 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 134 192 57 45 26 23 77 25 26.1 39 127 90 108
#> 17.81 16.44 14.46 17.42 15.77 16.92 7.27 6.32 15.77 15.59 3.53 20.94 18.29
#> 93 179 179.1 13 81 97 110 101 78 158 32 81.1 133
#> 10.33 18.63 18.63 14.34 14.06 19.14 17.56 9.97 23.88 20.14 20.90 14.06 14.65
#> 79 51 51.1 155 113 13.1 130 30 130.1 93.1 8 108.1 8.1
#> 16.23 18.23 18.23 13.08 22.86 14.34 16.47 17.43 16.47 10.33 18.43 18.29 18.43
#> 184 99 181 111 123 168 106 77.1 164 155.1 40 125 184.1
#> 17.77 21.19 16.46 17.45 13.00 23.72 16.67 7.27 23.60 13.08 18.00 15.65 17.77
#> 168.1 43 24 85 158.1 76 69 5 136 77.2 96 76.1 30.1
#> 23.72 12.10 23.89 16.44 20.14 19.22 23.23 16.43 21.83 7.27 14.54 19.22 17.43
#> 32.1 169 13.2 108.2 86 111.1 134.1 133.1 127.1 188 92 51.2 168.2
#> 20.90 22.41 14.34 18.29 23.81 17.45 17.81 14.65 3.53 16.16 22.92 18.23 23.72
#> 155.2 105 197 66 36 150 42 125.1 25.1 66.1 180 45.1 155.3
#> 13.08 19.75 21.60 22.13 21.19 20.33 12.43 15.65 6.32 22.13 14.82 17.42 13.08
#> 91 188.1 81.2 107 97.1 45.2 117 175 70 128 149 93.2 44
#> 5.33 16.16 14.06 11.18 19.14 17.42 17.46 21.91 7.38 20.35 8.37 10.33 24.00
#> 122 75 132 162 21 21.1 80 156 53 148 65 34 21.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 161 151 173 12 3 160 20 102 82 7 35 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 116 178 102.1 31 142 53.1 11 173.1 82.1 131 82.2 53.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 142.1 200 161.1 46 87 83 84 2 67 191 44.1 83.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.2 47 143 104 148.1 98 72 141 87.1 121 144 7.1 83.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 21.3 1 17 176 161.3 138 33 64 11.1 83.3 174.1 174.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.2 20.1 27 31.1 138.1 103 152 80.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[5]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01247234 0.87813198 0.71056073
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.37441764 0.03199333 -0.24038882
#> grade_iii, Cure model
#> 0.51046363
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 105.1 19.75 1 60 0 0
#> 16 8.71 1 71 0 1
#> 97 19.14 1 65 0 1
#> 107 11.18 1 54 1 0
#> 13 14.34 1 54 0 1
#> 169 22.41 1 46 0 0
#> 153 21.33 1 55 1 0
#> 183 9.24 1 67 1 0
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 158 20.14 1 74 1 0
#> 180 14.82 1 37 0 0
#> 105.2 19.75 1 60 0 0
#> 14 12.89 1 21 0 0
#> 187 9.92 1 39 1 0
#> 10 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 97.1 19.14 1 65 0 1
#> 88 18.37 1 47 0 0
#> 16.1 8.71 1 71 0 1
#> 24 23.89 1 38 0 0
#> 150 20.33 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 39 15.59 1 37 0 1
#> 145 10.07 1 65 1 0
#> 181 16.46 1 45 0 1
#> 18 15.21 1 49 1 0
#> 140 12.68 1 59 1 0
#> 32 20.90 1 37 1 0
#> 106 16.67 1 49 1 0
#> 68 20.62 1 44 0 0
#> 199 19.81 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 125 15.65 1 67 1 0
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 169.1 22.41 1 46 0 0
#> 105.3 19.75 1 60 0 0
#> 127 3.53 1 62 0 1
#> 134 17.81 1 47 1 0
#> 111 17.45 1 47 0 1
#> 139.1 21.49 1 63 1 0
#> 154 12.63 1 20 1 0
#> 171.1 16.57 1 41 0 1
#> 169.2 22.41 1 46 0 0
#> 108.1 18.29 1 39 0 1
#> 39.1 15.59 1 37 0 1
#> 197 21.60 1 69 1 0
#> 158.1 20.14 1 74 1 0
#> 30 17.43 1 78 0 0
#> 6 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 170 19.54 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 29 15.45 1 68 1 0
#> 197.1 21.60 1 69 1 0
#> 134.1 17.81 1 47 1 0
#> 123 13.00 1 44 1 0
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 159.1 10.55 1 50 0 1
#> 169.3 22.41 1 46 0 0
#> 127.1 3.53 1 62 0 1
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 99 21.19 1 38 0 1
#> 187.1 9.92 1 39 1 0
#> 8 18.43 1 32 0 0
#> 40 18.00 1 28 1 0
#> 76.1 19.22 1 54 0 1
#> 32.1 20.90 1 37 1 0
#> 90.1 20.94 1 50 0 1
#> 190 20.81 1 42 1 0
#> 125.1 15.65 1 67 1 0
#> 8.1 18.43 1 32 0 0
#> 76.2 19.22 1 54 0 1
#> 183.2 9.24 1 67 1 0
#> 175 21.91 1 43 0 0
#> 41 18.02 1 40 1 0
#> 125.2 15.65 1 67 1 0
#> 128 20.35 1 35 0 1
#> 166 19.98 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 123.1 13.00 1 44 1 0
#> 91.1 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 114 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 70 7.38 1 30 1 0
#> 45.1 17.42 1 54 0 1
#> 169.4 22.41 1 46 0 0
#> 59 10.16 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 86 23.81 1 58 0 1
#> 32.2 20.90 1 37 1 0
#> 123.2 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 90.2 20.94 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 127.2 3.53 1 62 0 1
#> 18.1 15.21 1 49 1 0
#> 164 23.60 1 76 0 1
#> 102 24.00 0 49 0 0
#> 148 24.00 0 61 1 0
#> 165 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 198 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 20 24.00 0 46 1 0
#> 193 24.00 0 45 0 1
#> 73 24.00 0 NA 0 1
#> 83 24.00 0 6 0 0
#> 75 24.00 0 21 1 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 75.1 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 102.1 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 196 24.00 0 19 0 0
#> 160 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 74.1 24.00 0 43 0 1
#> 151 24.00 0 42 0 0
#> 121.1 24.00 0 57 1 0
#> 148.1 24.00 0 61 1 0
#> 141 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 9.1 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 135 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 119 24.00 0 17 0 0
#> 64 24.00 0 43 0 0
#> 65 24.00 0 57 1 0
#> 75.2 24.00 0 21 1 0
#> 174 24.00 0 49 1 0
#> 143.1 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 138 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 22 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 138.1 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 1 24.00 0 23 1 0
#> 196.1 24.00 0 19 0 0
#> 151.1 24.00 0 42 0 0
#> 142.1 24.00 0 53 0 0
#> 121.2 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 2 24.00 0 9 0 0
#> 80.2 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 54.1 24.00 0 53 1 0
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 47 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 54.2 24.00 0 53 1 0
#> 116 24.00 0 58 0 1
#> 156.1 24.00 0 50 1 0
#> 84.1 24.00 0 39 0 1
#> 126.1 24.00 0 48 0 0
#> 2.1 24.00 0 9 0 0
#> 185 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 22.1 24.00 0 52 1 0
#> 142.2 24.00 0 53 0 0
#> 185.1 24.00 0 44 1 0
#> 126.2 24.00 0 48 0 0
#> 118.1 24.00 0 44 1 0
#> 198.2 24.00 0 66 0 1
#> 137.1 24.00 0 45 1 0
#> 1.1 24.00 0 23 1 0
#> 103.1 24.00 0 56 1 0
#> 20.1 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.37 NA NA NA
#> 2 age, Cure model 0.0320 NA NA NA
#> 3 grade_ii, Cure model -0.240 NA NA NA
#> 4 grade_iii, Cure model 0.510 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0125 NA NA NA
#> 2 grade_ii, Survival model 0.878 NA NA NA
#> 3 grade_iii, Survival model 0.711 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.37442 0.03199 -0.24039 0.51046
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.37441764 0.03199333 -0.24038882 0.51046363
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01247234 0.87813198 0.71056073
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.277711513 0.954057331 0.277711513 0.916896116 0.355813664 0.804648230
#> [7] 0.690092494 0.032293318 0.126517053 0.889199828 0.795132674 0.776088659
#> [13] 0.249851415 0.680404531 0.277711513 0.737846000 0.870613223 0.842245556
#> [19] 0.526191845 0.355813664 0.395965685 0.916896116 0.001107275 0.240524355
#> [25] 0.889199828 0.622892906 0.861172628 0.545662118 0.651751590 0.756976915
#> [31] 0.186278743 0.516283417 0.222074649 0.406344169 0.105478158 0.823466374
#> [37] 0.584498856 0.326539973 0.023992644 0.032293318 0.277711513 0.972467904
#> [43] 0.457126666 0.476695893 0.105478158 0.766584907 0.526191845 0.032293318
#> [49] 0.406344169 0.622892906 0.084041586 0.249851415 0.486555968 0.613135365
#> [55] 0.574772146 0.316440408 0.785580263 0.642086443 0.084041586 0.457126666
#> [61] 0.709504692 0.137316305 0.010272059 0.823466374 0.032293318 0.972467904
#> [67] 0.699775328 0.157485115 0.137316305 0.870613223 0.375713089 0.447087819
#> [73] 0.326539973 0.186278743 0.157485115 0.212952922 0.584498856 0.375713089
#> [79] 0.326539973 0.889199828 0.072497474 0.436889361 0.584498856 0.231357446
#> [85] 0.268216909 0.545662118 0.804648230 0.709504692 0.954057331 0.426579935
#> [91] 0.565021243 0.670767293 0.737846000 0.496541915 0.944815991 0.496541915
#> [97] 0.032293318 0.851724808 0.005519167 0.186278743 0.709504692 0.935515039
#> [103] 0.157485115 0.972467904 0.651751590 0.016821477 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000
#>
#> $Time
#> 105 91 105.1 16 97 107 13 169 153 183 49 42 158
#> 19.75 5.33 19.75 8.71 19.14 11.18 14.34 22.41 21.33 9.24 12.19 12.43 20.14
#> 180 105.2 14 187 10 171 97.1 88 16.1 24 150 183.1 39
#> 14.82 19.75 12.89 9.92 10.53 16.57 19.14 18.37 8.71 23.89 20.33 9.24 15.59
#> 145 181 18 140 32 106 68 108 139 159 125 76 15
#> 10.07 16.46 15.21 12.68 20.90 16.67 20.62 18.29 21.49 10.55 15.65 19.22 22.68
#> 169.1 105.3 127 134 111 139.1 154 171.1 169.2 108.1 39.1 197 158.1
#> 22.41 19.75 3.53 17.81 17.45 21.49 12.63 16.57 22.41 18.29 15.59 21.60 20.14
#> 30 6 188 170 56 29 197.1 134.1 123 36 168 159.1 169.3
#> 17.43 15.64 16.16 19.54 12.21 15.45 21.60 17.81 13.00 21.19 23.72 10.55 22.41
#> 127.1 81 90 99 187.1 8 40 76.1 32.1 90.1 190 125.1 8.1
#> 3.53 14.06 20.94 21.19 9.92 18.43 18.00 19.22 20.90 20.94 20.81 15.65 18.43
#> 76.2 183.2 175 41 125.2 128 166 181.1 107.1 123.1 91.1 51 5
#> 19.22 9.24 21.91 18.02 15.65 20.35 19.98 16.46 11.18 13.00 5.33 18.23 16.43
#> 157 14.1 45 70 45.1 169.4 61 86 32.2 123.2 149 90.2 127.2
#> 15.10 12.89 17.42 7.38 17.42 22.41 10.12 23.81 20.90 13.00 8.37 20.94 3.53
#> 18.1 164 102 148 165 34 198 156 121 9 198.1 20 193
#> 15.21 23.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 75 162 118 143 75.1 103 80 74 120 102.1 54 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 98 74.1 151 121.1 148.1 141 120.1 11 9.1 17 87 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 176 119 64 65 75.2 174 143.1 80.1 186 138 193.1 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 138.1 142 1 196.1 151.1 142.1 121.2 12 2 80.2 126 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 137 144 47 72 54.2 116 156.1 84.1 126.1 2.1 185 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 22.1 142.2 185.1 126.2 118.1 198.2 137.1 1.1 103.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[6]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007307508 0.760235421 0.470427039
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.451087068 0.004510584 0.272592389
#> grade_iii, Cure model
#> 1.057295398
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 68 20.62 1 44 0 0
#> 5 16.43 1 51 0 1
#> 86 23.81 1 58 0 1
#> 114 13.68 1 NA 0 0
#> 18 15.21 1 49 1 0
#> 155 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 24 23.89 1 38 0 0
#> 81 14.06 1 34 0 0
#> 25 6.32 1 34 1 0
#> 117 17.46 1 26 0 1
#> 150 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 40 18.00 1 28 1 0
#> 117.1 17.46 1 26 0 1
#> 124 9.73 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 8 18.43 1 32 0 0
#> 92 22.92 1 47 0 1
#> 88 18.37 1 47 0 0
#> 177 12.53 1 75 0 0
#> 4 17.64 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 32 20.90 1 37 1 0
#> 133 14.65 1 57 0 0
#> 184 17.77 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 10.1 10.53 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 189 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 59 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 40.1 18.00 1 28 1 0
#> 114.1 13.68 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 159 10.55 1 50 0 1
#> 130 16.47 1 53 0 1
#> 184.1 17.77 1 38 0 0
#> 184.2 17.77 1 38 0 0
#> 125 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 79 16.23 1 54 1 0
#> 139 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 4.1 17.64 1 NA 0 1
#> 4.2 17.64 1 NA 0 1
#> 92.1 22.92 1 47 0 1
#> 58 19.34 1 39 0 0
#> 63 22.77 1 31 1 0
#> 130.1 16.47 1 53 0 1
#> 78 23.88 1 43 0 0
#> 134 17.81 1 47 1 0
#> 24.2 23.89 1 38 0 0
#> 159.1 10.55 1 50 0 1
#> 189.1 10.51 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 134.1 17.81 1 47 1 0
#> 14.1 12.89 1 21 0 0
#> 70 7.38 1 30 1 0
#> 51 18.23 1 83 0 1
#> 106 16.67 1 49 1 0
#> 110.1 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 63.1 22.77 1 31 1 0
#> 69 23.23 1 25 0 1
#> 140 12.68 1 59 1 0
#> 167.1 15.55 1 56 1 0
#> 16.1 8.71 1 71 0 1
#> 15.1 22.68 1 48 0 0
#> 125.1 15.65 1 67 1 0
#> 114.2 13.68 1 NA 0 0
#> 40.2 18.00 1 28 1 0
#> 8.2 18.43 1 32 0 0
#> 159.2 10.55 1 50 0 1
#> 177.1 12.53 1 75 0 0
#> 199.1 19.81 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 189.2 10.51 1 NA 1 0
#> 183.2 9.24 1 67 1 0
#> 69.1 23.23 1 25 0 1
#> 136 21.83 1 43 0 1
#> 61 10.12 1 36 0 1
#> 97.1 19.14 1 65 0 1
#> 183.3 9.24 1 67 1 0
#> 51.1 18.23 1 83 0 1
#> 128.1 20.35 1 35 0 1
#> 113.1 22.86 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 58.1 19.34 1 39 0 0
#> 91 5.33 1 61 0 1
#> 134.2 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 168 23.72 1 70 0 0
#> 91.1 5.33 1 61 0 1
#> 4.3 17.64 1 NA 0 1
#> 25.1 6.32 1 34 1 0
#> 32.1 20.90 1 37 1 0
#> 158 20.14 1 74 1 0
#> 101 9.97 1 10 0 1
#> 114.3 13.68 1 NA 0 0
#> 197 21.60 1 69 1 0
#> 71 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 48 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 53 24.00 0 32 0 1
#> 146 24.00 0 63 1 0
#> 200 24.00 0 64 0 0
#> 71.1 24.00 0 51 0 0
#> 162 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 17 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 120 24.00 0 68 0 1
#> 95 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 146.1 24.00 0 63 1 0
#> 95.1 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 53.1 24.00 0 32 0 1
#> 28 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 67.1 24.00 0 25 0 0
#> 151 24.00 0 42 0 0
#> 185 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 200.1 24.00 0 64 0 0
#> 87 24.00 0 27 0 0
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 83 24.00 0 6 0 0
#> 173 24.00 0 19 0 1
#> 7.1 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 116 24.00 0 58 0 1
#> 46 24.00 0 71 0 0
#> 64.1 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 161.1 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 72 24.00 0 40 0 1
#> 198 24.00 0 66 0 1
#> 73.1 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 172.1 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 112 24.00 0 61 0 0
#> 115.1 24.00 0 NA 1 0
#> 20.1 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 21.1 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 83.1 24.00 0 6 0 0
#> 38 24.00 0 31 1 0
#> 126.2 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 48.1 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 163 24.00 0 66 0 0
#> 102.1 24.00 0 49 0 0
#> 72.1 24.00 0 40 0 1
#> 118.1 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 95.2 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 83.2 24.00 0 6 0 0
#> 21.2 24.00 0 47 0 0
#> 82 24.00 0 34 0 0
#> 7.2 24.00 0 37 1 0
#> 75.1 24.00 0 21 1 0
#> 186 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 185.1 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.451 NA NA NA
#> 2 age, Cure model 0.00451 NA NA NA
#> 3 grade_ii, Cure model 0.273 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00731 NA NA NA
#> 2 grade_ii, Survival model 0.760 NA NA NA
#> 3 grade_iii, Survival model 0.470 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.451087 0.004511 0.272592 1.057295
#>
#> Degrees of Freedom: 177 Total (i.e. Null); 174 Residual
#> Null Deviance: 246.2
#> Residual Deviance: 238.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.451087068 0.004510584 0.272592389 1.057295398
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007307508 0.760235421 0.470427039
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7237742 0.9258777 0.4980519 0.7802887 0.2070450 0.8306716 0.8597706
#> [8] 0.8062814 0.0804602 0.8540133 0.9811646 0.7383617 0.5306291 0.5093259
#> [15] 0.8482451 0.6542256 0.7383617 0.8655198 0.6000631 0.3042933 0.6275755
#> [22] 0.8936653 0.9046251 0.8826065 0.4755685 0.8365576 0.7012942 0.0804602
#> [29] 0.9258777 0.6000631 0.4059822 0.5813507 0.6542256 0.8125751 0.9469126
#> [36] 0.9469126 0.9100544 0.7667230 0.7012942 0.7012942 0.7936353 0.9666019
#> [43] 0.7870235 0.4631167 0.3404803 0.8246984 0.3042933 0.5616400 0.3756184
#> [50] 0.7667230 0.1716226 0.6785812 0.0804602 0.9100544 0.5306291 0.6785812
#> [57] 0.8655198 0.9763290 0.6368275 0.7526845 0.7237742 0.7597413 0.3756184
#> [64] 0.2617672 0.8769549 0.8125751 0.9666019 0.4059822 0.7936353 0.6542256
#> [71] 0.6000631 0.9100544 0.8936653 0.9469126 0.2617672 0.4354222 0.9364229
#> [78] 0.5813507 0.9469126 0.6368275 0.5093259 0.3404803 0.8826065 0.5616400
#> [85] 0.9906494 0.6785812 0.8424224 0.2354631 0.9906494 0.9811646 0.4755685
#> [92] 0.5515792 0.9416783 0.4498102 0.0000000 0.0000000 0.0000000 0.0000000
#> [99] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 110 10 68 5 86 18 155 39 24 81 25 117 150
#> 17.56 10.53 20.62 16.43 23.81 15.21 13.08 15.59 23.89 14.06 6.32 17.46 20.33
#> 128 13 40 117.1 14 8 92 88 177 49 154 32 133
#> 20.35 14.34 18.00 17.46 12.89 18.43 22.92 18.37 12.53 12.19 12.63 20.90 14.65
#> 184 24.1 10.1 8.1 15 97 40.1 167 183 183.1 159 130 184.1
#> 17.77 23.89 10.53 18.43 22.68 19.14 18.00 15.55 9.24 9.24 10.55 16.47 17.77
#> 184.2 125 16 79 139 113 29 92.1 58 63 130.1 78 134
#> 17.77 15.65 8.71 16.23 21.49 22.86 15.45 22.92 19.34 22.77 16.47 23.88 17.81
#> 24.2 159.1 150.1 134.1 14.1 70 51 106 110.1 171 63.1 69 140
#> 23.89 10.55 20.33 17.81 12.89 7.38 18.23 16.67 17.56 16.57 22.77 23.23 12.68
#> 167.1 16.1 15.1 125.1 40.2 8.2 159.2 177.1 183.2 69.1 136 61 97.1
#> 15.55 8.71 22.68 15.65 18.00 18.43 10.55 12.53 9.24 23.23 21.83 10.12 19.14
#> 183.3 51.1 128.1 113.1 154.1 58.1 91 134.2 96 168 91.1 25.1 32.1
#> 9.24 18.23 20.35 22.86 12.63 19.34 5.33 17.81 14.54 23.72 5.33 6.32 20.90
#> 158 101 197 71 126 20 132 75 48 156 67 53 146
#> 20.14 9.97 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 71.1 162 35 126.1 17 120 95 9 118 64 146.1 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 121 162.1 141 7 53.1 28 182 67.1 151 185 161 200.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 65 1 83 173 7.1 116 46 64.1 172 161.1 131 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 198 21 172.1 135 112 20.1 27 21.1 119 2 83.1 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 102 48.1 119.1 163 102.1 72.1 118.1 193 95.2 176 38.1 83.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.2 82 7.2 75.1 186 28.1 185.1 148 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[7]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008301942 0.574098655 0.426532493
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.96555828 0.02172000 0.04395919
#> grade_iii, Cure model
#> 0.53245735
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 81 14.06 1 34 0 0
#> 159 10.55 1 50 0 1
#> 113 22.86 1 34 0 0
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 61 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 37 12.52 1 57 1 0
#> 23 16.92 1 61 0 0
#> 32 20.90 1 37 1 0
#> 197 21.60 1 69 1 0
#> 76 19.22 1 54 0 1
#> 92.1 22.92 1 47 0 1
#> 40 18.00 1 28 1 0
#> 51 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 167.1 15.55 1 56 1 0
#> 5.1 16.43 1 51 0 1
#> 145 10.07 1 65 1 0
#> 93 10.33 1 52 0 1
#> 105 19.75 1 60 0 0
#> 18 15.21 1 49 1 0
#> 140.1 12.68 1 59 1 0
#> 107 11.18 1 54 1 0
#> 145.1 10.07 1 65 1 0
#> 153 21.33 1 55 1 0
#> 187 9.92 1 39 1 0
#> 18.1 15.21 1 49 1 0
#> 23.1 16.92 1 61 0 0
#> 127 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 164 23.60 1 76 0 1
#> 39 15.59 1 37 0 1
#> 29 15.45 1 68 1 0
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 91 5.33 1 61 0 1
#> 133 14.65 1 57 0 0
#> 58 19.34 1 39 0 0
#> 14 12.89 1 21 0 0
#> 181 16.46 1 45 0 1
#> 10 10.53 1 34 0 0
#> 5.2 16.43 1 51 0 1
#> 16 8.71 1 71 0 1
#> 100 16.07 1 60 0 0
#> 68 20.62 1 44 0 0
#> 14.1 12.89 1 21 0 0
#> 50 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 184 17.77 1 38 0 0
#> 168.1 23.72 1 70 0 0
#> 134 17.81 1 47 1 0
#> 164.1 23.60 1 76 0 1
#> 77 7.27 1 67 0 1
#> 14.2 12.89 1 21 0 0
#> 171 16.57 1 41 0 1
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 68.1 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 81.1 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 36 21.19 1 48 0 1
#> 10.1 10.53 1 34 0 0
#> 50.1 10.02 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 105.1 19.75 1 60 0 0
#> 68.2 20.62 1 44 0 0
#> 79 16.23 1 54 1 0
#> 106 16.67 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 23.2 16.92 1 61 0 0
#> 110 17.56 1 65 0 1
#> 8 18.43 1 32 0 0
#> 153.1 21.33 1 55 1 0
#> 159.1 10.55 1 50 0 1
#> 29.1 15.45 1 68 1 0
#> 167.2 15.55 1 56 1 0
#> 40.1 18.00 1 28 1 0
#> 14.3 12.89 1 21 0 0
#> 192 16.44 1 31 1 0
#> 61.1 10.12 1 36 0 1
#> 24 23.89 1 38 0 0
#> 8.1 18.43 1 32 0 0
#> 150 20.33 1 48 0 0
#> 96 14.54 1 33 0 1
#> 42 12.43 1 49 0 1
#> 45 17.42 1 54 0 1
#> 97.1 19.14 1 65 0 1
#> 5.3 16.43 1 51 0 1
#> 129.1 23.41 1 53 1 0
#> 92.2 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 153.2 21.33 1 55 1 0
#> 52 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 197.1 21.60 1 69 1 0
#> 76.1 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 37.1 12.52 1 57 1 0
#> 113.1 22.86 1 34 0 0
#> 76.2 19.22 1 54 0 1
#> 155 13.08 1 26 0 0
#> 114 13.68 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 58.1 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 24.1 23.89 1 38 0 0
#> 144 24.00 0 28 0 1
#> 176 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 196 24.00 0 19 0 0
#> 132 24.00 0 55 0 0
#> 11 24.00 0 42 0 1
#> 135 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 196.1 24.00 0 19 0 0
#> 142 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 48 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 193 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 20 24.00 0 46 1 0
#> 142.1 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 196.2 24.00 0 19 0 0
#> 102 24.00 0 49 0 0
#> 172.1 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 104 24.00 0 50 1 0
#> 34 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 142.2 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 72.1 24.00 0 40 0 1
#> 115.1 24.00 0 NA 1 0
#> 176.1 24.00 0 43 0 1
#> 142.3 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 35 24.00 0 51 0 0
#> 132.1 24.00 0 55 0 0
#> 142.4 24.00 0 53 0 0
#> 176.2 24.00 0 43 0 1
#> 75.1 24.00 0 21 1 0
#> 47 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 176.3 24.00 0 43 0 1
#> 84.1 24.00 0 39 0 1
#> 94 24.00 0 51 0 1
#> 33 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 74 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 132.2 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 48.1 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 142.5 24.00 0 53 0 0
#> 121.1 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 198 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 200 24.00 0 64 0 0
#> 84.2 24.00 0 39 0 1
#> 11.1 24.00 0 42 0 1
#> 200.1 24.00 0 64 0 0
#> 1 24.00 0 23 1 0
#> 38 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 3.2 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 156.1 24.00 0 50 1 0
#> 80.1 24.00 0 41 0 0
#> 73 24.00 0 NA 0 1
#> 3.3 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 98.1 24.00 0 34 1 0
#> 64 24.00 0 43 0 0
#> 27 24.00 0 63 1 0
#> 33.1 24.00 0 53 0 0
#> 9.1 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 132.3 24.00 0 55 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.966 NA NA NA
#> 2 age, Cure model 0.0217 NA NA NA
#> 3 grade_ii, Cure model 0.0440 NA NA NA
#> 4 grade_iii, Cure model 0.532 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00830 NA NA NA
#> 2 grade_ii, Survival model 0.574 NA NA NA
#> 3 grade_iii, Survival model 0.427 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.96556 0.02172 0.04396 0.53246
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.96555828 0.02172000 0.04395919 0.53245735
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008301942 0.574098655 0.426532493
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.708860476 0.854289860 0.107698791 0.612528813 0.786204542 0.912598360
#> [7] 0.083063434 0.805662266 0.467218062 0.205914390 0.144101090 0.314703813
#> [13] 0.083063434 0.409782474 0.399989729 0.545104083 0.612528813 0.545104083
#> [19] 0.931981853 0.902826190 0.268099677 0.660561819 0.786204542 0.844567293
#> [25] 0.931981853 0.162293065 0.951351232 0.660561819 0.467218062 0.990251622
#> [31] 0.020192205 0.037172695 0.602742757 0.641264341 0.380487997 0.249906295
#> [37] 0.980511339 0.679757221 0.295940492 0.747687930 0.515902151 0.873619330
#> [43] 0.545104083 0.961057476 0.592936521 0.223610471 0.747687930 0.188282689
#> [49] 0.438326578 0.020192205 0.428769017 0.037172695 0.970778480 0.747687930
#> [55] 0.506083399 0.012705672 0.286572376 0.699171768 0.073781703 0.223610471
#> [61] 0.728234849 0.708860476 0.342479263 0.188282689 0.873619330 0.055875089
#> [67] 0.268099677 0.223610471 0.583193504 0.496247483 0.134698421 0.467218062
#> [73] 0.447940863 0.361366960 0.162293065 0.854289860 0.641264341 0.612528813
#> [79] 0.409782474 0.747687930 0.525710760 0.912598360 0.003225667 0.361366960
#> [85] 0.258950462 0.689475756 0.825070258 0.457577272 0.342479263 0.545104083
#> [91] 0.055875089 0.083063434 0.390252039 0.162293065 0.893054566 0.834829701
#> [97] 0.144101090 0.314703813 0.525710760 0.805662266 0.107698791 0.314703813
#> [103] 0.737948944 0.214808472 0.295940492 0.125523888 0.003225667 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 81 159 113 167 140 61 92 37 23 32 197 76 92.1
#> 14.06 10.55 22.86 15.55 12.68 10.12 22.92 12.52 16.92 20.90 21.60 19.22 22.92
#> 40 51 5 167.1 5.1 145 93 105 18 140.1 107 145.1 153
#> 18.00 18.23 16.43 15.55 16.43 10.07 10.33 19.75 15.21 12.68 11.18 10.07 21.33
#> 187 18.1 23.1 127 168 164 39 29 88 128 91 133 58
#> 9.92 15.21 16.92 3.53 23.72 23.60 15.59 15.45 18.37 20.35 5.33 14.65 19.34
#> 14 181 10 5.2 16 100 68 14.1 99 184 168.1 134 164.1
#> 12.89 16.46 10.53 16.43 8.71 16.07 20.62 12.89 21.19 17.77 23.72 17.81 23.60
#> 77 14.2 171 78 170 57 69 68.1 60 81.1 97 36 10.1
#> 7.27 12.89 16.57 23.88 19.54 14.46 23.23 20.62 13.15 14.06 19.14 21.19 10.53
#> 129 105.1 68.2 79 106 66 23.2 110 8 153.1 159.1 29.1 167.2
#> 23.41 19.75 20.62 16.23 16.67 22.13 16.92 17.56 18.43 21.33 10.55 15.45 15.55
#> 40.1 14.3 192 61.1 24 8.1 150 96 42 45 97.1 5.3 129.1
#> 18.00 12.89 16.44 10.12 23.89 18.43 20.33 14.54 12.43 17.42 19.14 16.43 23.41
#> 92.2 108 153.2 52 49 197.1 76.1 85 37.1 113.1 76.2 155 190
#> 22.92 18.29 21.33 10.42 12.19 21.60 19.22 16.44 12.52 22.86 19.22 13.08 20.81
#> 58.1 194 24.1 144 176 3 72 112 196 132 11 135 174
#> 19.34 22.40 23.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196.1 142 172 48 135.1 193 121 84 20 142.1 75 196.2 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 98 104 34 142.2 126 160 156 72.1 176.1 142.3 71 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 142.4 176.2 75.1 47 80 191 176.3 84.1 94 33 17 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 94.1 132.2 44 48.1 9 142.5 121.1 47.1 198 65 200 84.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 200.1 1 38 3.1 131 46 87 3.2 109 156.1 80.1 3.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 146 103 98.1 64 27 33.1 9.1 173 132.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[8]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005116424 1.017401526 0.453873749
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.52174302 0.01269559 -0.57451361
#> grade_iii, Cure model
#> 0.73025853
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 105 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 113 22.86 1 34 0 0
#> 184 17.77 1 38 0 0
#> 49 12.19 1 48 1 0
#> 111 17.45 1 47 0 1
#> 188 16.16 1 46 0 1
#> 175 21.91 1 43 0 0
#> 49.1 12.19 1 48 1 0
#> 197 21.60 1 69 1 0
#> 159 10.55 1 50 0 1
#> 136 21.83 1 43 0 1
#> 155 13.08 1 26 0 0
#> 124 9.73 1 NA 1 0
#> 61 10.12 1 36 0 1
#> 195 11.76 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 32.1 20.90 1 37 1 0
#> 92 22.92 1 47 0 1
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 66 22.13 1 53 0 0
#> 96 14.54 1 33 0 1
#> 13 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 6 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 30 17.43 1 78 0 0
#> 58 19.34 1 39 0 0
#> 149 8.37 1 33 1 0
#> 123.1 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 37 12.52 1 57 1 0
#> 108 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 13.1 14.34 1 54 0 1
#> 90 20.94 1 50 0 1
#> 66.1 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 23 16.92 1 61 0 0
#> 96.1 14.54 1 33 0 1
#> 5 16.43 1 51 0 1
#> 100 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 86 23.81 1 58 0 1
#> 40 18.00 1 28 1 0
#> 97 19.14 1 65 0 1
#> 155.1 13.08 1 26 0 0
#> 45 17.42 1 54 0 1
#> 61.1 10.12 1 36 0 1
#> 136.1 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 154 12.63 1 20 1 0
#> 155.2 13.08 1 26 0 0
#> 99 21.19 1 38 0 1
#> 78 23.88 1 43 0 0
#> 128 20.35 1 35 0 1
#> 77 7.27 1 67 0 1
#> 123.2 13.00 1 44 1 0
#> 195.1 11.76 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 130 16.47 1 53 0 1
#> 60 13.15 1 38 1 0
#> 150.1 20.33 1 48 0 0
#> 113.1 22.86 1 34 0 0
#> 164.1 23.60 1 76 0 1
#> 130.1 16.47 1 53 0 1
#> 199 19.81 1 NA 0 1
#> 13.2 14.34 1 54 0 1
#> 10 10.53 1 34 0 0
#> 159.1 10.55 1 50 0 1
#> 183 9.24 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 159.2 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 183.1 9.24 1 67 1 0
#> 96.2 14.54 1 33 0 1
#> 99.1 21.19 1 38 0 1
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 150.2 20.33 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 23.1 16.92 1 61 0 0
#> 78.1 23.88 1 43 0 0
#> 150.3 20.33 1 48 0 0
#> 181 16.46 1 45 0 1
#> 81.1 14.06 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 86.1 23.81 1 58 0 1
#> 188.2 16.16 1 46 0 1
#> 78.2 23.88 1 43 0 0
#> 117.1 17.46 1 26 0 1
#> 188.3 16.16 1 46 0 1
#> 93 10.33 1 52 0 1
#> 85 16.44 1 36 0 0
#> 110 17.56 1 65 0 1
#> 59.1 10.16 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 159.3 10.55 1 50 0 1
#> 96.3 14.54 1 33 0 1
#> 30.1 17.43 1 78 0 0
#> 128.1 20.35 1 35 0 1
#> 77.1 7.27 1 67 0 1
#> 18 15.21 1 49 1 0
#> 101 9.97 1 10 0 1
#> 4.1 17.64 1 NA 0 1
#> 96.4 14.54 1 33 0 1
#> 158 20.14 1 74 1 0
#> 133 14.65 1 57 0 0
#> 185 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 11 24.00 0 42 0 1
#> 54 24.00 0 53 1 0
#> 196.1 24.00 0 19 0 0
#> 126 24.00 0 48 0 0
#> 174 24.00 0 49 1 0
#> 160 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 191 24.00 0 60 0 1
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 144 24.00 0 28 0 1
#> 67 24.00 0 25 0 0
#> 143 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 7 24.00 0 37 1 0
#> 196.2 24.00 0 19 0 0
#> 173 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 72 24.00 0 40 0 1
#> 142 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 2.1 24.00 0 9 0 0
#> 142.1 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 172 24.00 0 41 0 0
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 126.1 24.00 0 48 0 0
#> 67.1 24.00 0 25 0 0
#> 152 24.00 0 36 0 1
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 151 24.00 0 42 0 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 152.1 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 119 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 67.2 24.00 0 25 0 0
#> 137.1 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 27 24.00 0 63 1 0
#> 102 24.00 0 49 0 0
#> 137.2 24.00 0 45 1 0
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 147.1 24.00 0 76 1 0
#> 54.1 24.00 0 53 1 0
#> 72.2 24.00 0 40 0 1
#> 120 24.00 0 68 0 1
#> 152.2 24.00 0 36 0 1
#> 196.3 24.00 0 19 0 0
#> 103.1 24.00 0 56 1 0
#> 198 24.00 0 66 0 1
#> 62 24.00 0 71 0 0
#> 102.1 24.00 0 49 0 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 198.1 24.00 0 66 0 1
#> 200.1 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 72.3 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 20 24.00 0 46 1 0
#> 74 24.00 0 43 0 1
#> 102.2 24.00 0 49 0 0
#> 191.1 24.00 0 60 0 1
#> 160.1 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 11.1 24.00 0 42 0 1
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.522 NA NA NA
#> 2 age, Cure model 0.0127 NA NA NA
#> 3 grade_ii, Cure model -0.575 NA NA NA
#> 4 grade_iii, Cure model 0.730 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00512 NA NA NA
#> 2 grade_ii, Survival model 1.02 NA NA NA
#> 3 grade_iii, Survival model 0.454 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.5217 0.0127 -0.5745 0.7303
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52174302 0.01269559 -0.57451361 0.73025853
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005116424 1.017401526 0.453873749
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.262562323 0.361115665 0.440452716 0.131235149 0.421059051 0.860752614
#> [7] 0.459295592 0.573126740 0.179701778 0.860752614 0.216945398 0.876605865
#> [13] 0.192683472 0.769392675 0.923581414 0.106716200 0.262562323 0.119125022
#> [19] 0.401387734 0.302196135 0.795213207 0.155015772 0.674167752 0.717249182
#> [25] 0.646962505 0.628255056 0.351122632 0.468768992 0.371182348 0.969951099
#> [31] 0.795213207 0.082320323 0.637682651 0.828300146 0.391380523 0.006742728
#> [37] 0.717249182 0.251206928 0.155015772 0.743233487 0.506637562 0.674167752
#> [43] 0.563633612 0.609591619 0.057490750 0.411387568 0.381298675 0.769392675
#> [49] 0.487774636 0.923581414 0.192683472 0.836454775 0.820059004 0.769392675
#> [55] 0.228792866 0.022716144 0.282598574 0.977490316 0.795213207 0.487774636
#> [61] 0.525690728 0.760724389 0.302196135 0.131235149 0.082320323 0.525690728
#> [67] 0.717249182 0.907781068 0.876605865 0.954774248 0.609591619 0.876605865
#> [73] 0.992483540 0.954774248 0.674167752 0.228792866 0.947036475 0.302196135
#> [79] 0.836454775 0.506637562 0.022716144 0.302196135 0.544606552 0.743233487
#> [85] 0.573126740 0.057490750 0.573126740 0.022716144 0.440452716 0.573126740
#> [91] 0.915688282 0.554106342 0.430769954 0.852613912 0.876605865 0.674167752
#> [97] 0.468768992 0.282598574 0.977490316 0.656117192 0.939217851 0.674167752
#> [103] 0.341191164 0.665126982 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 32 105 117 113 184 49 111 188 175 49.1 197 159 136
#> 20.90 19.75 17.46 22.86 17.77 12.19 17.45 16.16 21.91 12.19 21.60 10.55 21.83
#> 155 61 69 32.1 92 51 150 123 66 96 13 29 6
#> 13.08 10.12 23.23 20.90 22.92 18.23 20.33 13.00 22.13 14.54 14.34 15.45 15.64
#> 166 30 58 149 123.1 164 167 37 108 24 13.1 90 66.1
#> 19.98 17.43 19.34 8.37 13.00 23.60 15.55 12.52 18.29 23.89 14.34 20.94 22.13
#> 81 23 96.1 5 100 86 40 97 155.1 45 61.1 136.1 42
#> 14.06 16.92 14.54 16.43 16.07 23.81 18.00 19.14 13.08 17.42 10.12 21.83 12.43
#> 154 155.2 99 78 128 77 123.2 45.1 130 60 150.1 113.1 164.1
#> 12.63 13.08 21.19 23.88 20.35 7.27 13.00 17.42 16.47 13.15 20.33 22.86 23.60
#> 130.1 13.2 10 159.1 183 100.1 159.2 91 183.1 96.2 99.1 187 150.2
#> 16.47 14.34 10.53 10.55 9.24 16.07 10.55 5.33 9.24 14.54 21.19 9.92 20.33
#> 42.1 23.1 78.1 150.3 181 81.1 188.1 86.1 188.2 78.2 117.1 188.3 93
#> 12.43 16.92 23.88 20.33 16.46 14.06 16.16 23.81 16.16 23.88 17.46 16.16 10.33
#> 85 110 56 159.3 96.3 30.1 128.1 77.1 18 101 96.4 158 133
#> 16.44 17.56 12.21 10.55 14.54 17.43 20.35 7.27 15.21 9.97 14.54 20.14 14.65
#> 185 178 196 11 54 196.1 126 174 160 137 87 191 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 21 28 46 144 67 143 165 53 7 196.2 173 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 142 200 2.1 142.1 28.1 172 147 176 75 126.1 67.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 118 72.1 151 19 9 156 152.1 22 119 65 3 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.2 137.1 103 27 102 137.2 33 148 135 147.1 54.1 72.2 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.2 196.3 103.1 198 62 102.1 146 1 198.1 200.1 94 72.3 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 74 102.2 191.1 160.1 19.1 31 11.1 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[9]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006257022 0.927522982 0.642993903
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.72696997 0.01075882 0.27343531
#> grade_iii, Cure model
#> 1.36591815
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 50 10.02 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 55 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 171 16.57 1 41 0 1
#> 177 12.53 1 75 0 0
#> 169 22.41 1 46 0 0
#> 194 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 93 10.33 1 52 0 1
#> 130 16.47 1 53 0 1
#> 56 12.21 1 60 0 0
#> 45 17.42 1 54 0 1
#> 128 20.35 1 35 0 1
#> 32 20.90 1 37 1 0
#> 130.1 16.47 1 53 0 1
#> 99 21.19 1 38 0 1
#> 41 18.02 1 40 1 0
#> 197 21.60 1 69 1 0
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 57 14.46 1 45 0 1
#> 140 12.68 1 59 1 0
#> 32.1 20.90 1 37 1 0
#> 159 10.55 1 50 0 1
#> 170.1 19.54 1 43 0 1
#> 166 19.98 1 48 0 0
#> 24 23.89 1 38 0 0
#> 30 17.43 1 78 0 0
#> 114 13.68 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 36 21.19 1 48 0 1
#> 106 16.67 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 187 9.92 1 39 1 0
#> 51 18.23 1 83 0 1
#> 171.1 16.57 1 41 0 1
#> 106.1 16.67 1 49 1 0
#> 15 22.68 1 48 0 0
#> 189 10.51 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 42 12.43 1 49 0 1
#> 68 20.62 1 44 0 0
#> 139 21.49 1 63 1 0
#> 36.1 21.19 1 48 0 1
#> 89 11.44 1 NA 0 0
#> 169.1 22.41 1 46 0 0
#> 40 18.00 1 28 1 0
#> 140.1 12.68 1 59 1 0
#> 128.1 20.35 1 35 0 1
#> 60.1 13.15 1 38 1 0
#> 155 13.08 1 26 0 0
#> 97 19.14 1 65 0 1
#> 111.1 17.45 1 47 0 1
#> 93.1 10.33 1 52 0 1
#> 8 18.43 1 32 0 0
#> 133 14.65 1 57 0 0
#> 169.2 22.41 1 46 0 0
#> 14 12.89 1 21 0 0
#> 51.1 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 41.1 18.02 1 40 1 0
#> 25 6.32 1 34 1 0
#> 169.3 22.41 1 46 0 0
#> 188 16.16 1 46 0 1
#> 16 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 130.2 16.47 1 53 0 1
#> 15.1 22.68 1 48 0 0
#> 52 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 175 21.91 1 43 0 0
#> 49 12.19 1 48 1 0
#> 43.1 12.10 1 61 0 1
#> 15.2 22.68 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 30.1 17.43 1 78 0 0
#> 145 10.07 1 65 1 0
#> 195 11.76 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 14.1 12.89 1 21 0 0
#> 110 17.56 1 65 0 1
#> 177.1 12.53 1 75 0 0
#> 158.1 20.14 1 74 1 0
#> 194.1 22.40 1 38 0 1
#> 32.2 20.90 1 37 1 0
#> 16.1 8.71 1 71 0 1
#> 194.2 22.40 1 38 0 1
#> 197.1 21.60 1 69 1 0
#> 154 12.63 1 20 1 0
#> 24.1 23.89 1 38 0 0
#> 184 17.77 1 38 0 0
#> 58 19.34 1 39 0 0
#> 169.4 22.41 1 46 0 0
#> 140.2 12.68 1 59 1 0
#> 37 12.52 1 57 1 0
#> 105.1 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 111.2 17.45 1 47 0 1
#> 187.1 9.92 1 39 1 0
#> 190 20.81 1 42 1 0
#> 36.2 21.19 1 48 0 1
#> 85.1 16.44 1 36 0 0
#> 57.1 14.46 1 45 0 1
#> 123.1 13.00 1 44 1 0
#> 123.2 13.00 1 44 1 0
#> 142 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 53 24.00 0 32 0 1
#> 148 24.00 0 61 1 0
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 116 24.00 0 58 0 1
#> 196 24.00 0 19 0 0
#> 109 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 64 24.00 0 43 0 0
#> 185.1 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 131 24.00 0 66 0 0
#> 118.1 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 102.2 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 120 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 22 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 152 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 176 24.00 0 43 0 1
#> 121 24.00 0 57 1 0
#> 83.1 24.00 0 6 0 0
#> 54.1 24.00 0 53 1 0
#> 122 24.00 0 66 0 0
#> 80.1 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 163 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 122.1 24.00 0 66 0 0
#> 122.2 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 147 24.00 0 76 1 0
#> 198 24.00 0 66 0 1
#> 186.1 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 148.1 24.00 0 61 1 0
#> 160 24.00 0 31 1 0
#> 7 24.00 0 37 1 0
#> 161 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 121.1 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 185.2 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 73.1 24.00 0 NA 0 1
#> 132.1 24.00 0 55 0 0
#> 182 24.00 0 35 0 0
#> 34 24.00 0 36 0 0
#> 12.1 24.00 0 63 0 0
#> 120.1 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 132.2 24.00 0 55 0 0
#> 83.2 24.00 0 6 0 0
#> 172.1 24.00 0 41 0 0
#> 142.1 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 196.1 24.00 0 19 0 0
#> 144 24.00 0 28 0 1
#> 33.1 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 138 24.00 0 44 1 0
#> 160.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 83.3 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.727 NA NA NA
#> 2 age, Cure model 0.0108 NA NA NA
#> 3 grade_ii, Cure model 0.273 NA NA NA
#> 4 grade_iii, Cure model 1.37 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00626 NA NA NA
#> 2 grade_ii, Survival model 0.928 NA NA NA
#> 3 grade_iii, Survival model 0.643 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.72697 0.01076 0.27344 1.36592
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.72696997 0.01075882 0.27343531 1.36591815
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006257022 0.927522982 0.642993903
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84102411 0.64641968 0.63111945 0.77092398 0.90359889 0.28162172
#> [7] 0.37716353 0.99231499 0.95615195 0.78224633 0.92165146 0.75332183
#> [13] 0.57344289 0.52638338 0.78224633 0.48371500 0.68991266 0.44355581
#> [19] 0.13936792 0.79858504 0.82548768 0.88519964 0.52638338 0.93914628
#> [25] 0.63111945 0.60716195 0.06335354 0.74114431 0.18075783 0.48371500
#> [31] 0.75935381 0.59102651 0.96859519 0.67599979 0.77092398 0.75935381
#> [37] 0.21133737 0.72276406 0.91718797 0.56419161 0.47088511 0.48371500
#> [43] 0.28162172 0.70322239 0.88519964 0.57344289 0.84102411 0.85108813
#> [49] 0.66133074 0.72276406 0.95615195 0.66867418 0.82019410 0.28162172
#> [55] 0.87556521 0.67599979 0.85108813 0.68991266 0.99617326 0.28162172
#> [61] 0.80947734 0.98455168 0.61524612 0.78224633 0.21133737 0.95192121
#> [67] 0.83583964 0.93050767 0.42660471 0.92610512 0.93050767 0.21133737
#> [73] 0.93914628 0.74114431 0.96447466 0.97666613 0.81488584 0.97666613
#> [79] 0.87556521 0.71632837 0.90359889 0.59102651 0.37716353 0.52638338
#> [85] 0.98455168 0.37716353 0.44355581 0.89901426 0.06335354 0.70978350
#> [91] 0.64641968 0.28162172 0.88519964 0.91268980 0.61524612 0.94765953
#> [97] 0.86113116 0.72276406 0.96859519 0.55489200 0.48371500 0.79858504
#> [103] 0.82548768 0.86113116 0.86113116 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 60 55 170 171 177 169 194 70 93 130 56 45 128
#> 13.15 19.34 19.54 16.57 12.53 22.41 22.40 7.38 10.33 16.47 12.21 17.42 20.35
#> 32 130.1 99 41 197 78 85 57 140 32.1 159 170.1 166
#> 20.90 16.47 21.19 18.02 21.60 23.88 16.44 14.46 12.68 20.90 10.55 19.54 19.98
#> 24 30 92 36 106 158 187 51 171.1 106.1 15 111 42
#> 23.89 17.43 22.92 21.19 16.67 20.14 9.92 18.23 16.57 16.67 22.68 17.45 12.43
#> 68 139 36.1 169.1 40 140.1 128.1 60.1 155 97 111.1 93.1 8
#> 20.62 21.49 21.19 22.41 18.00 12.68 20.35 13.15 13.08 19.14 17.45 10.33 18.43
#> 133 169.2 14 51.1 155.1 41.1 25 169.3 188 16 105 130.2 15.1
#> 14.65 22.41 12.89 18.23 13.08 18.02 6.32 22.41 16.16 8.71 19.75 16.47 22.68
#> 52 81 43 175 49 43.1 15.2 159.1 30.1 145 183 125 183.1
#> 10.42 14.06 12.10 21.91 12.19 12.10 22.68 10.55 17.43 10.07 9.24 15.65 9.24
#> 14.1 110 177.1 158.1 194.1 32.2 16.1 194.2 197.1 154 24.1 184 58
#> 12.89 17.56 12.53 20.14 22.40 20.90 8.71 22.40 21.60 12.63 23.89 17.77 19.34
#> 169.4 140.2 37 105.1 10 123 111.2 187.1 190 36.2 85.1 57.1 123.1
#> 22.41 12.68 12.52 19.75 10.53 13.00 17.45 9.92 20.81 21.19 16.44 14.46 13.00
#> 123.2 142 53 148 118 185 116 196 109 102 64 185.1 19
#> 13.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 118.1 27 102.1 102.2 80 83 35 17 82 165 120 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 186 152 1 176 121 83.1 54.1 122 80.1 137 2 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 3 132 122.1 122.2 3.1 137.1 75 147 198 186.1 200 165.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 148.1 160 7 161 112 121.1 12 185.2 7.1 132.1 182 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 120.1 156 33 131.1 84 74 132.2 83.2 172.1 142.1 119 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 33.1 126 138 160.1 135 83.3 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[10]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003560704 0.525967272 0.295351249
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88981952 0.01887195 0.08575189
#> grade_iii, Cure model
#> 0.39751566
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 111 17.45 1 47 0 1
#> 140 12.68 1 59 1 0
#> 99 21.19 1 38 0 1
#> 167 15.55 1 56 1 0
#> 58 19.34 1 39 0 0
#> 69 23.23 1 25 0 1
#> 10 10.53 1 34 0 0
#> 111.1 17.45 1 47 0 1
#> 125 15.65 1 67 1 0
#> 32 20.90 1 37 1 0
#> 140.1 12.68 1 59 1 0
#> 189 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 32.1 20.90 1 37 1 0
#> 4 17.64 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 86 23.81 1 58 0 1
#> 36 21.19 1 48 0 1
#> 77 7.27 1 67 0 1
#> 127 3.53 1 62 0 1
#> 125.1 15.65 1 67 1 0
#> 56.1 12.21 1 60 0 0
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 30 17.43 1 78 0 0
#> 81 14.06 1 34 0 0
#> 158 20.14 1 74 1 0
#> 127.1 3.53 1 62 0 1
#> 89.1 11.44 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 13.1 14.34 1 54 0 1
#> 149 8.37 1 33 1 0
#> 133.1 14.65 1 57 0 0
#> 110 17.56 1 65 0 1
#> 18 15.21 1 49 1 0
#> 133.2 14.65 1 57 0 0
#> 8 18.43 1 32 0 0
#> 58.1 19.34 1 39 0 0
#> 106.1 16.67 1 49 1 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 180 14.82 1 37 0 0
#> 58.2 19.34 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 145 10.07 1 65 1 0
#> 51 18.23 1 83 0 1
#> 129 23.41 1 53 1 0
#> 77.2 7.27 1 67 0 1
#> 85 16.44 1 36 0 0
#> 90 20.94 1 50 0 1
#> 42 12.43 1 49 0 1
#> 187 9.92 1 39 1 0
#> 150 20.33 1 48 0 0
#> 14 12.89 1 21 0 0
#> 179 18.63 1 42 0 0
#> 197 21.60 1 69 1 0
#> 97.2 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 8.1 18.43 1 32 0 0
#> 70 7.38 1 30 1 0
#> 155 13.08 1 26 0 0
#> 88 18.37 1 47 0 0
#> 159 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 55 19.34 1 69 0 1
#> 89.2 11.44 1 NA 0 0
#> 125.2 15.65 1 67 1 0
#> 125.3 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 181 16.46 1 45 0 1
#> 129.1 23.41 1 53 1 0
#> 134 17.81 1 47 1 0
#> 164 23.60 1 76 0 1
#> 89.3 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 171 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 4.1 17.64 1 NA 0 1
#> 149.1 8.37 1 33 1 0
#> 18.1 15.21 1 49 1 0
#> 16 8.71 1 71 0 1
#> 187.1 9.92 1 39 1 0
#> 24.1 23.89 1 38 0 0
#> 55.1 19.34 1 69 0 1
#> 70.1 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 133.3 14.65 1 57 0 0
#> 66 22.13 1 53 0 0
#> 139 21.49 1 63 1 0
#> 18.2 15.21 1 49 1 0
#> 81.1 14.06 1 34 0 0
#> 70.2 7.38 1 30 1 0
#> 128 20.35 1 35 0 1
#> 168 23.72 1 70 0 0
#> 197.1 21.60 1 69 1 0
#> 10.1 10.53 1 34 0 0
#> 93 10.33 1 52 0 1
#> 23.1 16.92 1 61 0 0
#> 85.1 16.44 1 36 0 0
#> 171.1 16.57 1 41 0 1
#> 154 12.63 1 20 1 0
#> 68 20.62 1 44 0 0
#> 24.2 23.89 1 38 0 0
#> 113 22.86 1 34 0 0
#> 149.2 8.37 1 33 1 0
#> 140.2 12.68 1 59 1 0
#> 195 11.76 1 NA 1 0
#> 98 24.00 0 34 1 0
#> 38 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 9 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 75 24.00 0 21 1 0
#> 80 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 53 24.00 0 32 0 1
#> 83 24.00 0 6 0 0
#> 118.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 120 24.00 0 68 0 1
#> 196.1 24.00 0 19 0 0
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 178.1 24.00 0 52 1 0
#> 147 24.00 0 76 1 0
#> 185.1 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 120.1 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 83.1 24.00 0 6 0 0
#> 27 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 11 24.00 0 42 0 1
#> 64 24.00 0 43 0 0
#> 1 24.00 0 23 1 0
#> 160 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 156.1 24.00 0 50 1 0
#> 104 24.00 0 50 1 0
#> 198.1 24.00 0 66 0 1
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 118.2 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 163.1 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 31.1 24.00 0 36 0 1
#> 178.2 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 64.1 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 34.1 24.00 0 36 0 0
#> 102 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 173 24.00 0 19 0 1
#> 95.1 24.00 0 68 0 1
#> 53.1 24.00 0 32 0 1
#> 132.1 24.00 0 55 0 0
#> 46 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 9.1 24.00 0 31 1 0
#> 21.1 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 121 24.00 0 57 1 0
#> 17.1 24.00 0 38 0 1
#> 33.1 24.00 0 53 0 0
#> 64.2 24.00 0 43 0 0
#> 191.1 24.00 0 60 0 1
#> 142 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 33.2 24.00 0 53 0 0
#> 182.1 24.00 0 35 0 0
#> 121.1 24.00 0 57 1 0
#> 3 24.00 0 31 1 0
#> 46.1 24.00 0 71 0 0
#> 2 24.00 0 9 0 0
#> 54 24.00 0 53 1 0
#> 3.1 24.00 0 31 1 0
#> 11.2 24.00 0 42 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.890 NA NA NA
#> 2 age, Cure model 0.0189 NA NA NA
#> 3 grade_ii, Cure model 0.0858 NA NA NA
#> 4 grade_iii, Cure model 0.398 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00356 NA NA NA
#> 2 grade_ii, Survival model 0.526 NA NA NA
#> 3 grade_iii, Survival model 0.295 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88982 0.01887 0.08575 0.39752
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88981952 0.01887195 0.08575189 0.39751566
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003560704 0.525967272 0.295351249
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.48542780 0.43635770 0.73929419 0.19051528 0.60013391 0.29096927
#> [7] 0.10202445 0.82202155 0.43635770 0.56288213 0.22148957 0.73929419
#> [13] 0.22148957 0.78520136 0.04092307 0.19051528 0.94771244 0.98256656
#> [19] 0.56288213 0.78520136 0.64638954 0.68320539 0.45581554 0.70181306
#> [25] 0.27107782 0.98256656 0.87692948 0.68320539 0.89506452 0.64638954
#> [31] 0.42645694 0.60961366 0.64638954 0.37679491 0.29096927 0.48542780
#> [37] 0.33798034 0.33798034 0.63708188 0.29096927 0.94771244 0.84962818
#> [43] 0.40652220 0.08022407 0.94771244 0.53379758 0.21103314 0.77600259
#> [49] 0.85882217 0.26104970 0.72988132 0.36686510 0.15852799 0.33798034
#> [55] 0.80357348 0.37679491 0.92158417 0.72047718 0.39650346 0.81280403
#> [61] 0.55310802 0.29096927 0.56288213 0.56288213 0.28099588 0.52409608
#> [67] 0.08022407 0.41654100 0.06692601 0.01302416 0.50482153 0.13563107
#> [73] 0.89506452 0.60961366 0.88599901 0.85882217 0.01302416 0.29096927
#> [79] 0.92158417 0.97379873 0.46570230 0.11328824 0.64638954 0.14700268
#> [85] 0.17978346 0.60961366 0.70181306 0.92158417 0.25108177 0.05357061
#> [91] 0.15852799 0.82202155 0.84039999 0.46570230 0.53379758 0.50482153
#> [97] 0.76678978 0.24103968 0.01302416 0.12440217 0.89506452 0.73929419
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 106 111 140 99 167 58 69 10 111.1 125 32 140.1 32.1
#> 16.67 17.45 12.68 21.19 15.55 19.34 23.23 10.53 17.45 15.65 20.90 12.68 20.90
#> 56 86 36 77 127 125.1 56.1 133 13 30 81 158 127.1
#> 12.21 23.81 21.19 7.27 3.53 15.65 12.21 14.65 14.34 17.43 14.06 20.14 3.53
#> 183 13.1 149 133.1 110 18 133.2 8 58.1 106.1 97 97.1 180
#> 9.24 14.34 8.37 14.65 17.56 15.21 14.65 18.43 19.34 16.67 19.14 19.14 14.82
#> 58.2 77.1 145 51 129 77.2 85 90 42 187 150 14 179
#> 19.34 7.27 10.07 18.23 23.41 7.27 16.44 20.94 12.43 9.92 20.33 12.89 18.63
#> 197 97.2 43 8.1 70 155 88 159 100 55 125.2 125.3 166
#> 21.60 19.14 12.10 18.43 7.38 13.08 18.37 10.55 16.07 19.34 15.65 15.65 19.98
#> 181 129.1 134 164 24 171 169 149.1 18.1 16 187.1 24.1 55.1
#> 16.46 23.41 17.81 23.60 23.89 16.57 22.41 8.37 15.21 8.71 9.92 23.89 19.34
#> 70.1 91 23 92 133.3 66 139 18.2 81.1 70.2 128 168 197.1
#> 7.38 5.33 16.92 22.92 14.65 22.13 21.49 15.21 14.06 7.38 20.35 23.72 21.60
#> 10.1 93 23.1 85.1 171.1 154 68 24.2 113 149.2 140.2 98 38
#> 10.53 10.33 16.92 16.44 16.57 12.63 20.62 23.89 22.86 8.37 12.68 24.00 24.00
#> 196 9 191 132 178 35 156 118 62 17 75 80 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 83 118.1 34 120 196.1 95 185 163 178.1 147 185.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 83.1 27 31 200 11 64 1 160 11.1 156.1 104 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 21 118.2 112 163.1 71 137 31.1 178.2 162 33 64.1 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 143 138 34.1 102 109 7 173 95.1 53.1 132.1 46 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 9.1 21.1 44 121 17.1 33.1 64.2 191.1 142 22 33.2 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121.1 3 46.1 2 54 3.1 11.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[11]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01116671 0.71543809 0.25866025
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.06251935 0.01822288 0.30803827
#> grade_iii, Cure model
#> 1.05894897
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 85 16.44 1 36 0 0
#> 180 14.82 1 37 0 0
#> 90 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 79 16.23 1 54 1 0
#> 77 7.27 1 67 0 1
#> 86 23.81 1 58 0 1
#> 166 19.98 1 48 0 0
#> 60 13.15 1 38 1 0
#> 49 12.19 1 48 1 0
#> 51 18.23 1 83 0 1
#> 68 20.62 1 44 0 0
#> 192 16.44 1 31 1 0
#> 181 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 6 15.64 1 39 0 0
#> 108 18.29 1 39 0 1
#> 134 17.81 1 47 1 0
#> 58 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 60.1 13.15 1 38 1 0
#> 86.1 23.81 1 58 0 1
#> 192.1 16.44 1 31 1 0
#> 68.1 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 179 18.63 1 42 0 0
#> 89 11.44 1 NA 0 0
#> 5 16.43 1 51 0 1
#> 52 10.42 1 52 0 1
#> 25 6.32 1 34 1 0
#> 18 15.21 1 49 1 0
#> 113 22.86 1 34 0 0
#> 69 23.23 1 25 0 1
#> 192.2 16.44 1 31 1 0
#> 97 19.14 1 65 0 1
#> 100 16.07 1 60 0 0
#> 42.1 12.43 1 49 0 1
#> 190 20.81 1 42 1 0
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 187 9.92 1 39 1 0
#> 60.2 13.15 1 38 1 0
#> 145.1 10.07 1 65 1 0
#> 117.1 17.46 1 26 0 1
#> 145.2 10.07 1 65 1 0
#> 40 18.00 1 28 1 0
#> 66.1 22.13 1 53 0 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 43 12.10 1 61 0 1
#> 85.1 16.44 1 36 0 0
#> 154 12.63 1 20 1 0
#> 133 14.65 1 57 0 0
#> 158 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 123 13.00 1 44 1 0
#> 61 10.12 1 36 0 1
#> 158.1 20.14 1 74 1 0
#> 175 21.91 1 43 0 0
#> 197 21.60 1 69 1 0
#> 199 19.81 1 NA 0 1
#> 14 12.89 1 21 0 0
#> 85.2 16.44 1 36 0 0
#> 110.1 17.56 1 65 0 1
#> 150 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 125 15.65 1 67 1 0
#> 79.1 16.23 1 54 1 0
#> 153 21.33 1 55 1 0
#> 10 10.53 1 34 0 0
#> 77.1 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 157 15.10 1 47 0 0
#> 6.1 15.64 1 39 0 0
#> 158.2 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 36 21.19 1 48 0 1
#> 29 15.45 1 68 1 0
#> 61.1 10.12 1 36 0 1
#> 43.1 12.10 1 61 0 1
#> 56 12.21 1 60 0 0
#> 158.3 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 134.1 17.81 1 47 1 0
#> 24.1 23.89 1 38 0 0
#> 96 14.54 1 33 0 1
#> 79.2 16.23 1 54 1 0
#> 136 21.83 1 43 0 1
#> 168 23.72 1 70 0 0
#> 76 19.22 1 54 0 1
#> 130 16.47 1 53 0 1
#> 92 22.92 1 47 0 1
#> 164.1 23.60 1 76 0 1
#> 180.1 14.82 1 37 0 0
#> 36.1 21.19 1 48 0 1
#> 140 12.68 1 59 1 0
#> 18.1 15.21 1 49 1 0
#> 45 17.42 1 54 0 1
#> 149 8.37 1 33 1 0
#> 42.2 12.43 1 49 0 1
#> 194.1 22.40 1 38 0 1
#> 101 9.97 1 10 0 1
#> 129.1 23.41 1 53 1 0
#> 199.1 19.81 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 96.1 14.54 1 33 0 1
#> 50.1 10.02 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 74 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 148 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 62 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 19 24.00 0 57 0 1
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 126 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 62.1 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 74.1 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 48 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 165 24.00 0 47 0 0
#> 173 24.00 0 19 0 1
#> 174.1 24.00 0 49 1 0
#> 27.1 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 156.1 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 34 24.00 0 36 0 0
#> 73.1 24.00 0 NA 0 1
#> 196.1 24.00 0 19 0 0
#> 137 24.00 0 45 1 0
#> 126.1 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 120.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 143.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 67 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 156.2 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 160.1 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 196.2 24.00 0 19 0 0
#> 102 24.00 0 49 0 0
#> 121 24.00 0 57 1 0
#> 119 24.00 0 17 0 0
#> 72 24.00 0 40 0 1
#> 141.1 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 28.1 24.00 0 67 1 0
#> 156.3 24.00 0 50 1 0
#> 141.2 24.00 0 44 1 0
#> 172.1 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 142.1 24.00 0 53 0 0
#> 126.2 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 193.2 24.00 0 45 0 1
#> 94.2 24.00 0 51 0 1
#> 161 24.00 0 45 0 0
#> 75.1 24.00 0 21 1 0
#> 121.1 24.00 0 57 1 0
#> 160.2 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 62.2 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 20 24.00 0 46 1 0
#> 141.3 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 82.1 24.00 0 34 0 0
#> 126.3 24.00 0 48 0 0
#> 131.1 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0182 NA NA NA
#> 3 grade_ii, Cure model 0.308 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0112 NA NA NA
#> 2 grade_ii, Survival model 0.715 NA NA NA
#> 3 grade_iii, Survival model 0.259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06252 0.01822 0.30804 1.05895
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 251.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.06251935 0.01822288 0.30803827 1.05894897
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01116671 0.71543809 0.25866025
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.425413902 0.617069653 0.157053143 0.334316884 0.503945683 0.967597544
#> [7] 0.007491311 0.236363447 0.680803807 0.806685506 0.294750985 0.174564454
#> [13] 0.425413902 0.415043244 0.354162002 0.554725725 0.284760702 0.314902108
#> [19] 0.245796019 0.881616464 0.680803807 0.007491311 0.425413902 0.174564454
#> [25] 0.764755359 0.754288309 0.083204951 0.274826937 0.483517548 0.849320530
#> [31] 0.989191021 0.585953895 0.061613600 0.047736560 0.425413902 0.265025824
#> [37] 0.534060156 0.764755359 0.165873304 0.035081957 0.021865073 0.924495454
#> [43] 0.680803807 0.881616464 0.354162002 0.881616464 0.304909082 0.083204951
#> [49] 0.384197614 0.132389280 0.817297072 0.425413902 0.743809317 0.638092102
#> [55] 0.201376769 0.068920097 0.394487459 0.712102770 0.860107060 0.201376769
#> [61] 0.098680539 0.115466439 0.722653049 0.425413902 0.334316884 0.192178817
#> [67] 0.670036928 0.544389780 0.503945683 0.123958512 0.838571585 0.967597544
#> [73] 0.001624452 0.606589267 0.554725725 0.201376769 0.132389280 0.575475545
#> [79] 0.860107060 0.817297072 0.796046435 0.201376769 0.946018808 0.314902108
#> [85] 0.001624452 0.648774914 0.503945683 0.107007960 0.015871618 0.255358176
#> [91] 0.404728369 0.054571563 0.021865073 0.617069653 0.132389280 0.733235625
#> [97] 0.585953895 0.374042135 0.956833403 0.764755359 0.068920097 0.913695166
#> [103] 0.035081957 0.483517548 0.648774914 0.935255137 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 85 180 90 110 79 77 86 166 60 49 51 68 192
#> 16.44 14.82 20.94 17.56 16.23 7.27 23.81 19.98 13.15 12.19 18.23 20.62 16.44
#> 181 117 6 108 134 58 145 60.1 86.1 192.1 68.1 42 37
#> 16.46 17.46 15.64 18.29 17.81 19.34 10.07 13.15 23.81 16.44 20.62 12.43 12.52
#> 66 179 5 52 25 18 113 69 192.2 97 100 42.1 190
#> 22.13 18.63 16.43 10.42 6.32 15.21 22.86 23.23 16.44 19.14 16.07 12.43 20.81
#> 129 164 187 60.2 145.1 117.1 145.2 40 66.1 23 99 43 85.1
#> 23.41 23.60 9.92 13.15 10.07 17.46 10.07 18.00 22.13 16.92 21.19 12.10 16.44
#> 154 133 158 194 106 123 61 158.1 175 197 14 85.2 110.1
#> 12.63 14.65 20.14 22.40 16.67 13.00 10.12 20.14 21.91 21.60 12.89 16.44 17.56
#> 150 13 125 79.1 153 10 77.1 24 157 6.1 158.2 36 29
#> 20.33 14.34 15.65 16.23 21.33 10.53 7.27 23.89 15.10 15.64 20.14 21.19 15.45
#> 61.1 43.1 56 158.3 16 134.1 24.1 96 79.2 136 168 76 130
#> 10.12 12.10 12.21 20.14 8.71 17.81 23.89 14.54 16.23 21.83 23.72 19.22 16.47
#> 92 164.1 180.1 36.1 140 18.1 45 149 42.2 194.1 101 129.1 5.1
#> 22.92 23.60 14.82 21.19 12.68 15.21 17.42 8.37 12.43 22.40 9.97 23.41 16.43
#> 96.1 183 74 9 172 27 174 148 151 83 62 98 19
#> 14.54 9.24 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 196 126 28 62.1 143 74.1 94 48 120 131 156 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 11 165 173 174.1 27.1 35 156.1 33 82 34 196.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1 137.1 120.1 176 143.1 141 83.1 67 75 94.1 156.2 193 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 196.2 102 121 119 72 141.1 185 3 193.1 28.1 156.3 141.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 47 142.1 126.2 122 182 193.2 94.2 161 75.1 121.1 160.2 3.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.2 109 191 20 141.3 75.2 82.1 126.3 131.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[12]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004639595 0.010062915 -0.017878748
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.88527716 0.01912927 -0.22506670
#> grade_iii, Cure model
#> 0.61389293
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 127 3.53 1 62 0 1
#> 4 17.64 1 NA 0 1
#> 97 19.14 1 65 0 1
#> 14 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 85 16.44 1 36 0 0
#> 14.1 12.89 1 21 0 0
#> 117 17.46 1 26 0 1
#> 129 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 43 12.10 1 61 0 1
#> 14.2 12.89 1 21 0 0
#> 150 20.33 1 48 0 0
#> 180 14.82 1 37 0 0
#> 127.1 3.53 1 62 0 1
#> 127.2 3.53 1 62 0 1
#> 58 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 68 20.62 1 44 0 0
#> 189 10.51 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 145 10.07 1 65 1 0
#> 189.1 10.51 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 190 20.81 1 42 1 0
#> 195 11.76 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 155 13.08 1 26 0 0
#> 51 18.23 1 83 0 1
#> 50 10.02 1 NA 1 0
#> 4.1 17.64 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 42 12.43 1 49 0 1
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 150.1 20.33 1 48 0 0
#> 157 15.10 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 26 15.77 1 49 0 1
#> 169.1 22.41 1 46 0 0
#> 93 10.33 1 52 0 1
#> 136.1 21.83 1 43 0 1
#> 51.1 18.23 1 83 0 1
#> 68.1 20.62 1 44 0 0
#> 170 19.54 1 43 0 1
#> 195.2 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 32 20.90 1 37 1 0
#> 14.3 12.89 1 21 0 0
#> 117.1 17.46 1 26 0 1
#> 155.1 13.08 1 26 0 0
#> 106 16.67 1 49 1 0
#> 6 15.64 1 39 0 0
#> 192 16.44 1 31 1 0
#> 190.1 20.81 1 42 1 0
#> 124 9.73 1 NA 1 0
#> 93.1 10.33 1 52 0 1
#> 59 10.16 1 NA 1 0
#> 37.1 12.52 1 57 1 0
#> 5 16.43 1 51 0 1
#> 158 20.14 1 74 1 0
#> 123 13.00 1 44 1 0
#> 194 22.40 1 38 0 1
#> 158.1 20.14 1 74 1 0
#> 97.1 19.14 1 65 0 1
#> 101 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 58.1 19.34 1 39 0 0
#> 133 14.65 1 57 0 0
#> 106.1 16.67 1 49 1 0
#> 175 21.91 1 43 0 0
#> 99 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 43.1 12.10 1 61 0 1
#> 23 16.92 1 61 0 0
#> 86 23.81 1 58 0 1
#> 128 20.35 1 35 0 1
#> 158.2 20.14 1 74 1 0
#> 123.1 13.00 1 44 1 0
#> 187 9.92 1 39 1 0
#> 153 21.33 1 55 1 0
#> 107 11.18 1 54 1 0
#> 42.1 12.43 1 49 0 1
#> 96.1 14.54 1 33 0 1
#> 60 13.15 1 38 1 0
#> 153.1 21.33 1 55 1 0
#> 37.2 12.52 1 57 1 0
#> 169.2 22.41 1 46 0 0
#> 69 23.23 1 25 0 1
#> 76 19.22 1 54 0 1
#> 133.1 14.65 1 57 0 0
#> 188.1 16.16 1 46 0 1
#> 93.2 10.33 1 52 0 1
#> 43.2 12.10 1 61 0 1
#> 180.1 14.82 1 37 0 0
#> 26.1 15.77 1 49 0 1
#> 117.2 17.46 1 26 0 1
#> 129.1 23.41 1 53 1 0
#> 128.1 20.35 1 35 0 1
#> 177 12.53 1 75 0 0
#> 99.1 21.19 1 38 0 1
#> 58.2 19.34 1 39 0 0
#> 128.2 20.35 1 35 0 1
#> 183 9.24 1 67 1 0
#> 125 15.65 1 67 1 0
#> 188.2 16.16 1 46 0 1
#> 124.1 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 79 16.23 1 54 1 0
#> 180.2 14.82 1 37 0 0
#> 147 24.00 0 76 1 0
#> 31 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 162 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 141 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 12 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 22 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 143 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 87 24.00 0 27 0 0
#> 48 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 118 24.00 0 44 1 0
#> 173 24.00 0 19 0 1
#> 147.1 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 103 24.00 0 56 1 0
#> 146.1 24.00 0 63 1 0
#> 152.1 24.00 0 36 0 1
#> 73 24.00 0 NA 0 1
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 53.2 24.00 0 32 0 1
#> 151 24.00 0 42 0 0
#> 173.1 24.00 0 19 0 1
#> 156.1 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 28 24.00 0 67 1 0
#> 102 24.00 0 49 0 0
#> 22.1 24.00 0 52 1 0
#> 9.1 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 135.1 24.00 0 58 1 0
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 53.3 24.00 0 32 0 1
#> 173.2 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 193.1 24.00 0 45 0 1
#> 160.2 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 17 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 109 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 27 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 131 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 38 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 131.1 24.00 0 66 0 0
#> 118.1 24.00 0 44 1 0
#> 131.2 24.00 0 66 0 0
#> 64.1 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 104 24.00 0 50 1 0
#> 38.1 24.00 0 31 1 0
#> 173.3 24.00 0 19 0 1
#> 172.1 24.00 0 41 0 0
#> 182.1 24.00 0 35 0 0
#> 172.2 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 102.1 24.00 0 49 0 0
#> 137.1 24.00 0 45 1 0
#> 72.1 24.00 0 40 0 1
#> 191 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.885 NA NA NA
#> 2 age, Cure model 0.0191 NA NA NA
#> 3 grade_ii, Cure model -0.225 NA NA NA
#> 4 grade_iii, Cure model 0.614 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00464 NA NA NA
#> 2 grade_ii, Survival model 0.0101 NA NA NA
#> 3 grade_iii, Survival model -0.0179 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88528 0.01913 -0.22507 0.61389
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.1
#> Residual Deviance: 248.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.88527716 0.01912927 -0.22506670 0.61389293
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004639595 0.010062915 -0.017878748
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.962821889 0.287772347 0.711589498 0.006025203 0.431457996 0.711589498
#> [7] 0.358500976 0.012060656 0.630594565 0.828703203 0.711589498 0.186184066
#> [13] 0.574101872 0.962821889 0.962821889 0.240875964 0.474541275 0.143309306
#> [19] 0.348106761 0.913298981 0.063378477 0.126519723 0.078108076 0.665189948
#> [25] 0.317560110 0.030227304 0.804817117 0.551474507 0.769481560 0.186184066
#> [31] 0.562765905 0.307491747 0.506962254 0.030227304 0.876871505 0.063378477
#> [37] 0.317560110 0.143309306 0.231334331 0.240875964 0.118024877 0.711589498
#> [43] 0.358500976 0.665189948 0.399682303 0.540228085 0.431457996 0.126519723
#> [49] 0.876871505 0.769481560 0.452785611 0.204084400 0.688320723 0.048594568
#> [55] 0.204084400 0.287772347 0.925648670 0.337796746 0.240875964 0.607751404
#> [61] 0.399682303 0.055897552 0.101814616 0.828703203 0.389124252 0.001589723
#> [67] 0.160472102 0.204084400 0.688320723 0.938008627 0.086051572 0.864674262
#> [73] 0.804817117 0.630594565 0.653568601 0.086051572 0.769481560 0.030227304
#> [79] 0.023383628 0.277925724 0.607751404 0.474541275 0.876871505 0.828703203
#> [85] 0.574101872 0.506962254 0.358500976 0.012060656 0.160472102 0.757642132
#> [91] 0.101814616 0.240875964 0.160472102 0.950394221 0.529020290 0.474541275
#> [97] 0.420734043 0.463636163 0.574101872 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 127 97 14 164 85 14.1 117 129 96 43 14.2 150 180
#> 3.53 19.14 12.89 23.60 16.44 12.89 17.46 23.41 14.54 12.10 12.89 20.33 14.82
#> 127.1 127.2 58 188 68 110 145 136 190 139 155 51 169
#> 3.53 3.53 19.34 16.16 20.62 17.56 10.07 21.83 20.81 21.49 13.08 18.23 22.41
#> 42 18 37 150.1 157 8 26 169.1 93 136.1 51.1 68.1 170
#> 12.43 15.21 12.52 20.33 15.10 18.43 15.77 22.41 10.33 21.83 18.23 20.62 19.54
#> 55 32 14.3 117.1 155.1 106 6 192 190.1 93.1 37.1 5 158
#> 19.34 20.90 12.89 17.46 13.08 16.67 15.64 16.44 20.81 10.33 12.52 16.43 20.14
#> 123 194 158.1 97.1 101 40 58.1 133 106.1 175 99 43.1 23
#> 13.00 22.40 20.14 19.14 9.97 18.00 19.34 14.65 16.67 21.91 21.19 12.10 16.92
#> 86 128 158.2 123.1 187 153 107 42.1 96.1 60 153.1 37.2 169.2
#> 23.81 20.35 20.14 13.00 9.92 21.33 11.18 12.43 14.54 13.15 21.33 12.52 22.41
#> 69 76 133.1 188.1 93.2 43.2 180.1 26.1 117.2 129.1 128.1 177 99.1
#> 23.23 19.22 14.65 16.16 10.33 12.10 14.82 15.77 17.46 23.41 20.35 12.53 21.19
#> 58.2 128.2 183 125 188.2 130 79 180.2 147 31 138 152 156
#> 19.34 20.35 9.24 15.65 16.16 16.47 16.23 14.82 24.00 24.00 24.00 24.00 24.00
#> 162 83 141 141.1 112 12 135 22 193 143 71 146 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 87 48 53.1 64 118 173 147.1 172 72 103 146.1 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 82 74 185 53.2 151 173.1 156.1 163 176 28 102 22.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 160 160.1 135.1 120 144 53.3 173.2 95 193.1 160.2 1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 83.1 132 44 75 109 12.1 27 137 131 119.1 38 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 131.1 118.1 131.2 64.1 182 104 38.1 173.3 172.1 182.1 172.2 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 137.1 72.1 191
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[13]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001474762 0.728357890 0.401428607
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05875917 0.01784179 0.07914340
#> grade_iii, Cure model
#> 1.03366049
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 164 23.60 1 76 0 1
#> 154 12.63 1 20 1 0
#> 89 11.44 1 NA 0 0
#> 166 19.98 1 48 0 0
#> 89.1 11.44 1 NA 0 0
#> 184 17.77 1 38 0 0
#> 85 16.44 1 36 0 0
#> 42 12.43 1 49 0 1
#> 51 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 99.1 21.19 1 38 0 1
#> 171 16.57 1 41 0 1
#> 52 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 50 10.02 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 127.1 3.53 1 62 0 1
#> 105 19.75 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 63 22.77 1 31 1 0
#> 26 15.77 1 49 0 1
#> 92 22.92 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 107 11.18 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 134 17.81 1 47 1 0
#> 127.2 3.53 1 62 0 1
#> 23 16.92 1 61 0 0
#> 81 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 60 13.15 1 38 1 0
#> 106.1 16.67 1 49 1 0
#> 25 6.32 1 34 1 0
#> 59 10.16 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 68 20.62 1 44 0 0
#> 26.1 15.77 1 49 0 1
#> 92.1 22.92 1 47 0 1
#> 168 23.72 1 70 0 0
#> 155 13.08 1 26 0 0
#> 197 21.60 1 69 1 0
#> 130 16.47 1 53 0 1
#> 91 5.33 1 61 0 1
#> 68.1 20.62 1 44 0 0
#> 78 23.88 1 43 0 0
#> 4 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 51.1 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 136 21.83 1 43 0 1
#> 79 16.23 1 54 1 0
#> 187 9.92 1 39 1 0
#> 59.1 10.16 1 NA 1 0
#> 130.1 16.47 1 53 0 1
#> 86 23.81 1 58 0 1
#> 37 12.52 1 57 1 0
#> 88.1 18.37 1 47 0 0
#> 105.2 19.75 1 60 0 0
#> 179 18.63 1 42 0 0
#> 51.2 18.23 1 83 0 1
#> 101 9.97 1 10 0 1
#> 15 22.68 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 195 11.76 1 NA 1 0
#> 134.1 17.81 1 47 1 0
#> 60.1 13.15 1 38 1 0
#> 89.2 11.44 1 NA 0 0
#> 139 21.49 1 63 1 0
#> 184.1 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 61 10.12 1 36 0 1
#> 40 18.00 1 28 1 0
#> 91.1 5.33 1 61 0 1
#> 39.1 15.59 1 37 0 1
#> 107.2 11.18 1 54 1 0
#> 69.1 23.23 1 25 0 1
#> 192 16.44 1 31 1 0
#> 130.2 16.47 1 53 0 1
#> 13 14.34 1 54 0 1
#> 68.2 20.62 1 44 0 0
#> 99.2 21.19 1 38 0 1
#> 50.1 10.02 1 NA 1 0
#> 15.1 22.68 1 48 0 0
#> 145 10.07 1 65 1 0
#> 23.1 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 52.2 10.42 1 52 0 1
#> 4.1 17.64 1 NA 0 1
#> 189.1 10.51 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 111 17.45 1 47 0 1
#> 52.3 10.42 1 52 0 1
#> 42.1 12.43 1 49 0 1
#> 192.1 16.44 1 31 1 0
#> 145.1 10.07 1 65 1 0
#> 88.2 18.37 1 47 0 0
#> 49.2 12.19 1 48 1 0
#> 153 21.33 1 55 1 0
#> 18 15.21 1 49 1 0
#> 180 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 52.4 10.42 1 52 0 1
#> 91.2 5.33 1 61 0 1
#> 114.2 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 137 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 31 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 9.1 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 165.1 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 22 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 31.1 24.00 0 36 0 1
#> 62 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 148 24.00 0 61 1 0
#> 109 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 148.2 24.00 0 61 1 0
#> 119 24.00 0 17 0 0
#> 196 24.00 0 19 0 0
#> 74 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 115 24.00 0 NA 1 0
#> 109.1 24.00 0 48 0 0
#> 80 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 119.1 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 185 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 65 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 94.1 24.00 0 51 0 1
#> 103.1 24.00 0 56 1 0
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 148.3 24.00 0 61 1 0
#> 142.1 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 94.2 24.00 0 51 0 1
#> 144.1 24.00 0 28 0 1
#> 71.1 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 104.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 138 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 200 24.00 0 64 0 0
#> 28 24.00 0 67 1 0
#> 200.1 24.00 0 64 0 0
#> 7.1 24.00 0 37 1 0
#> 176.1 24.00 0 43 0 1
#> 132 24.00 0 55 0 0
#> 119.2 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 156.1 24.00 0 50 1 0
#> 138.1 24.00 0 44 1 0
#> 82.1 24.00 0 34 0 0
#> 138.2 24.00 0 44 1 0
#> 115.2 24.00 0 NA 1 0
#> 64.1 24.00 0 43 0 0
#> 163 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 165.2 24.00 0 47 0 0
#> 137.2 24.00 0 45 1 0
#> 87.1 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 95.1 24.00 0 68 0 1
#> 191 24.00 0 60 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0178 NA NA NA
#> 3 grade_ii, Cure model 0.0791 NA NA NA
#> 4 grade_iii, Cure model 1.03 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00147 NA NA NA
#> 2 grade_ii, Survival model 0.728 NA NA NA
#> 3 grade_iii, Survival model 0.401 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05876 0.01784 0.07914 1.03366
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250
#> Residual Deviance: 237.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05875917 0.01784179 0.07914340 1.03366049
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001474762 0.728357890 0.401428607
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.81901562 0.27973271 0.97840617 0.08166985 0.78605750 0.34276042
#> [7] 0.51141991 0.63729800 0.80268382 0.44990720 0.10175679 0.41794819
#> [13] 0.27973271 0.59993887 0.87413318 0.82722961 0.70005841 0.97840617
#> [19] 0.35366429 0.87413318 0.17718748 0.68240028 0.13320157 0.35366429
#> [25] 0.85097637 0.85097637 0.49157450 0.97840617 0.56109707 0.75220194
#> [31] 0.58081890 0.76082623 0.58081890 0.94926412 0.55117824 0.31114501
#> [37] 0.68240028 0.13320157 0.05982047 0.77761424 0.23217092 0.60951376
#> [43] 0.95663777 0.31114501 0.01336963 0.53130748 0.44990720 0.38562216
#> [49] 0.21844586 0.67342221 0.94183446 0.60951376 0.03880132 0.79441001
#> [55] 0.41794819 0.35366429 0.39647320 0.44990720 0.93434836 0.19119260
#> [61] 0.23217092 0.49157450 0.76082623 0.25639353 0.51141991 0.82722961
#> [67] 0.91175474 0.48115308 0.95663777 0.70005841 0.85097637 0.10175679
#> [73] 0.63729800 0.60951376 0.74358249 0.31114501 0.27973271 0.19119260
#> [79] 0.91937974 0.56109707 0.73492494 0.87413318 0.39647320 0.54127878
#> [85] 0.87413318 0.80268382 0.63729800 0.91937974 0.41794819 0.82722961
#> [91] 0.26829397 0.71753381 0.72622661 0.66433350 0.87413318 0.95663777
#> [97] 0.16200907 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000
#>
#> $Time
#> 56 99 127 164 154 166 184 85 42 51 69 88 99.1
#> 12.21 21.19 3.53 23.60 12.63 19.98 17.77 16.44 12.43 18.23 23.23 18.37 21.19
#> 171 52 49 39 127.1 105 52.1 63 26 92 105.1 107 107.1
#> 16.57 10.42 12.19 15.59 3.53 19.75 10.42 22.77 15.77 22.92 19.75 11.18 11.18
#> 134 127.2 23 81 106 60 106.1 25 30 68 26.1 92.1 168
#> 17.81 3.53 16.92 14.06 16.67 13.15 16.67 6.32 17.43 20.62 15.77 22.92 23.72
#> 155 197 130 91 68.1 78 110 51.1 97 136 79 187 130.1
#> 13.08 21.60 16.47 5.33 20.62 23.88 17.56 18.23 19.14 21.83 16.23 9.92 16.47
#> 86 37 88.1 105.2 179 51.2 101 15 197.1 134.1 60.1 139 184.1
#> 23.81 12.52 18.37 19.75 18.63 18.23 9.97 22.68 21.60 17.81 13.15 21.49 17.77
#> 49.1 61 40 91.1 39.1 107.2 69.1 192 130.2 13 68.2 99.2 15.1
#> 12.19 10.12 18.00 5.33 15.59 11.18 23.23 16.44 16.47 14.34 20.62 21.19 22.68
#> 145 23.1 57 52.2 179.1 111 52.3 42.1 192.1 145.1 88.2 49.2 153
#> 10.07 16.92 14.46 10.42 18.63 17.45 10.42 12.43 16.44 10.07 18.37 12.19 21.33
#> 18 180 5 52.4 91.2 113 137 9 103 31 161 165 176
#> 15.21 14.82 16.43 10.42 5.33 22.86 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 118 71 82 165.1 121 20 198 22 21 31.1 62 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 109 137.1 48 148.1 142 75 148.2 119 196 74 12 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 144 119.1 156 186 174 185 104 94 65 11 94.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 98 148.3 142.1 95 47 35 94.2 144.1 71.1 35.1 161.1 104.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 182 138 200 28 200.1 7.1 176.1 132 119.2 87 156.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 138.2 64.1 163 122 165.2 137.2 87.1 34 53 95.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[14]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01980604 0.61824664 0.54831944
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.03696227 0.02169511 -0.08301693
#> grade_iii, Cure model
#> 0.94670953
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 179 18.63 1 42 0 0
#> 39 15.59 1 37 0 1
#> 59 10.16 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 184 17.77 1 38 0 0
#> 45 17.42 1 54 0 1
#> 13 14.34 1 54 0 1
#> 61 10.12 1 36 0 1
#> 79 16.23 1 54 1 0
#> 76 19.22 1 54 0 1
#> 194 22.40 1 38 0 1
#> 60 13.15 1 38 1 0
#> 88 18.37 1 47 0 0
#> 111 17.45 1 47 0 1
#> 187 9.92 1 39 1 0
#> 6 15.64 1 39 0 0
#> 170 19.54 1 43 0 1
#> 197 21.60 1 69 1 0
#> 189 10.51 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 168 23.72 1 70 0 0
#> 168.1 23.72 1 70 0 0
#> 159 10.55 1 50 0 1
#> 88.1 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 154 12.63 1 20 1 0
#> 133.1 14.65 1 57 0 0
#> 179.1 18.63 1 42 0 0
#> 29 15.45 1 68 1 0
#> 134 17.81 1 47 1 0
#> 169 22.41 1 46 0 0
#> 167 15.55 1 56 1 0
#> 18 15.21 1 49 1 0
#> 133.2 14.65 1 57 0 0
#> 18.1 15.21 1 49 1 0
#> 189.1 10.51 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 92 22.92 1 47 0 1
#> 88.2 18.37 1 47 0 0
#> 100 16.07 1 60 0 0
#> 177 12.53 1 75 0 0
#> 101 9.97 1 10 0 1
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 175 21.91 1 43 0 0
#> 187.1 9.92 1 39 1 0
#> 10 10.53 1 34 0 0
#> 110 17.56 1 65 0 1
#> 61.1 10.12 1 36 0 1
#> 23 16.92 1 61 0 0
#> 108 18.29 1 39 0 1
#> 66.1 22.13 1 53 0 0
#> 192 16.44 1 31 1 0
#> 10.1 10.53 1 34 0 0
#> 93 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 101.1 9.97 1 10 0 1
#> 99 21.19 1 38 0 1
#> 37 12.52 1 57 1 0
#> 123 13.00 1 44 1 0
#> 188 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 59.1 10.16 1 NA 1 0
#> 29.1 15.45 1 68 1 0
#> 155 13.08 1 26 0 0
#> 192.1 16.44 1 31 1 0
#> 113 22.86 1 34 0 0
#> 26 15.77 1 49 0 1
#> 168.2 23.72 1 70 0 0
#> 189.2 10.51 1 NA 1 0
#> 113.1 22.86 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 100.1 16.07 1 60 0 0
#> 4 17.64 1 NA 0 1
#> 29.2 15.45 1 68 1 0
#> 85 16.44 1 36 0 0
#> 130.1 16.47 1 53 0 1
#> 129 23.41 1 53 1 0
#> 194.1 22.40 1 38 0 1
#> 189.3 10.51 1 NA 1 0
#> 93.2 10.33 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 81 14.06 1 34 0 0
#> 158 20.14 1 74 1 0
#> 76.1 19.22 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 70 7.38 1 30 1 0
#> 36 21.19 1 48 0 1
#> 15 22.68 1 48 0 0
#> 93.3 10.33 1 52 0 1
#> 157 15.10 1 47 0 0
#> 57 14.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 5 16.43 1 51 0 1
#> 37.2 12.52 1 57 1 0
#> 93.4 10.33 1 52 0 1
#> 155.1 13.08 1 26 0 0
#> 68 20.62 1 44 0 0
#> 101.2 9.97 1 10 0 1
#> 154.1 12.63 1 20 1 0
#> 175.1 21.91 1 43 0 0
#> 153 21.33 1 55 1 0
#> 114.1 13.68 1 NA 0 0
#> 41 18.02 1 40 1 0
#> 51.1 18.23 1 83 0 1
#> 159.1 10.55 1 50 0 1
#> 155.2 13.08 1 26 0 0
#> 96 14.54 1 33 0 1
#> 128 20.35 1 35 0 1
#> 189.4 10.51 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 72 24.00 0 40 0 1
#> 74 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 9 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 12.1 24.00 0 63 0 0
#> 138 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 75 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 161 24.00 0 45 0 0
#> 48.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 20.2 24.00 0 46 1 0
#> 3 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 82 24.00 0 34 0 0
#> 71 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 98 24.00 0 34 1 0
#> 21.1 24.00 0 47 0 0
#> 103.1 24.00 0 56 1 0
#> 80 24.00 0 41 0 0
#> 138.1 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 112 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 148 24.00 0 61 1 0
#> 31.1 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 7.1 24.00 0 37 1 0
#> 21.2 24.00 0 47 0 0
#> 148.1 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 148.2 24.00 0 61 1 0
#> 185 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 3.1 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 176.1 24.00 0 43 0 1
#> 103.2 24.00 0 56 1 0
#> 173 24.00 0 19 0 1
#> 2 24.00 0 9 0 0
#> 12.2 24.00 0 63 0 0
#> 74.1 24.00 0 43 0 1
#> 73.2 24.00 0 NA 0 1
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 98.1 24.00 0 34 1 0
#> 35.2 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 7.2 24.00 0 37 1 0
#> 182 24.00 0 35 0 0
#> 163.1 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 44.1 24.00 0 56 0 0
#> 196 24.00 0 19 0 0
#> 31.2 24.00 0 36 0 1
#> 178.1 24.00 0 52 1 0
#> 182.1 24.00 0 35 0 0
#> 185.1 24.00 0 44 1 0
#> 75.2 24.00 0 21 1 0
#> 64.1 24.00 0 43 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.04 NA NA NA
#> 2 age, Cure model 0.0217 NA NA NA
#> 3 grade_ii, Cure model -0.0830 NA NA NA
#> 4 grade_iii, Cure model 0.947 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0198 NA NA NA
#> 2 grade_ii, Survival model 0.618 NA NA NA
#> 3 grade_iii, Survival model 0.548 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03696 0.02170 -0.08302 0.94671
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 245.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03696227 0.02169511 -0.08301693 0.94670953
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01980604 0.61824664 0.54831944
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.144537e-01 3.658813e-01 9.529041e-01 1.934067e-01 2.209558e-01
#> [6] 5.272583e-01 8.451140e-01 3.001176e-01 1.013348e-01 1.584451e-02
#> [11] 5.545975e-01 1.284815e-01 2.116153e-01 9.220936e-01 3.544286e-01
#> [16] 9.489933e-02 4.073845e-02 9.842209e-01 2.356497e-05 2.356497e-05
#> [21] 7.096497e-01 1.284815e-01 4.616010e-01 6.242440e-01 4.616010e-01
#> [26] 1.144537e-01 3.890463e-01 1.846255e-01 1.291650e-02 3.773949e-01
#> [31] 4.245675e-01 4.616010e-01 4.245675e-01 8.103855e-03 2.630262e-03
#> [36] 1.284815e-01 3.212701e-01 6.521323e-01 8.764820e-01 2.152786e-02
#> [41] 2.839381e-02 9.220936e-01 7.391697e-01 2.024040e-01 8.451140e-01
#> [46] 2.304596e-01 1.511254e-01 2.152786e-02 2.600449e-01 7.391697e-01
#> [51] 7.692790e-01 1.591704e-01 2.402463e-01 8.764820e-01 6.038454e-02
#> [56] 6.664684e-01 6.099804e-01 3.106391e-01 5.000037e-02 3.890463e-01
#> [61] 5.683948e-01 2.600449e-01 4.252433e-03 3.431715e-01 2.356497e-05
#> [66] 4.252433e-03 7.692790e-01 3.212701e-01 3.890463e-01 2.600449e-01
#> [71] 2.402463e-01 1.287265e-03 1.584451e-02 7.692790e-01 6.664684e-01
#> [76] 5.408433e-01 8.251836e-02 1.013348e-01 4.073845e-02 9.685656e-01
#> [81] 6.038454e-02 1.033875e-02 7.692790e-01 4.490022e-01 5.138140e-01
#> [86] 3.637020e-02 2.897285e-01 6.664684e-01 7.692790e-01 5.683948e-01
#> [91] 7.094975e-02 8.764820e-01 6.242440e-01 2.839381e-02 5.510047e-02
#> [96] 1.759551e-01 1.591704e-01 7.096497e-01 5.683948e-01 5.004712e-01
#> [101] 7.670455e-02 8.857615e-02 0.000000e+00 0.000000e+00 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 179 39 183 184 45 13 61 79 76 194 60 88 111
#> 18.63 15.59 9.24 17.77 17.42 14.34 10.12 16.23 19.22 22.40 13.15 18.37 17.45
#> 187 6 170 197 127 168 168.1 159 88.1 133 154 133.1 179.1
#> 9.92 15.64 19.54 21.60 3.53 23.72 23.72 10.55 18.37 14.65 12.63 14.65 18.63
#> 29 134 169 167 18 133.2 18.1 63 92 88.2 100 177 101
#> 15.45 17.81 22.41 15.55 15.21 14.65 15.21 22.77 22.92 18.37 16.07 12.53 9.97
#> 66 175 187.1 10 110 61.1 23 108 66.1 192 10.1 93 51
#> 22.13 21.91 9.92 10.53 17.56 10.12 16.92 18.29 22.13 16.44 10.53 10.33 18.23
#> 130 101.1 99 37 123 188 139 29.1 155 192.1 113 26 168.2
#> 16.47 9.97 21.19 12.52 13.00 16.16 21.49 15.45 13.08 16.44 22.86 15.77 23.72
#> 113.1 93.1 100.1 29.2 85 130.1 129 194.1 93.2 37.1 81 158 76.1
#> 22.86 10.33 16.07 15.45 16.44 16.47 23.41 22.40 10.33 12.52 14.06 20.14 19.22
#> 197.1 70 36 15 93.3 157 57 136 5 37.2 93.4 155.1 68
#> 21.60 7.38 21.19 22.68 10.33 15.10 14.46 21.83 16.43 12.52 10.33 13.08 20.62
#> 101.2 154.1 175.1 153 41 51.1 159.1 155.2 96 128 166 72 74
#> 9.97 12.63 21.91 21.33 18.02 18.23 10.55 13.08 14.54 20.35 19.98 24.00 24.00
#> 20 156 20.1 9 38 48 12 12.1 138 72.1 75 191 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 178 83 103 152 21 165 165.1 119 46 31 67 20.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 176 143 137 163 44 82 71 120 19 98 21.1 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 138.1 75.1 112 7 148 31.1 65 7.1 21.2 148.1 87 148.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 62 151 35 9.1 3.1 35.1 176.1 103.2 173 2 12.2 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 47 142 98.1 35.2 64 7.2 182 163.1 53 44.1 196 31.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 182.1 185.1 75.2 64.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[15]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009198519 0.311090196 0.172129053
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.63852430 0.01278549 -0.33761059
#> grade_iii, Cure model
#> 1.09078195
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 81 14.06 1 34 0 0
#> 16 8.71 1 71 0 1
#> 16.1 8.71 1 71 0 1
#> 26 15.77 1 49 0 1
#> 177 12.53 1 75 0 0
#> 40 18.00 1 28 1 0
#> 97 19.14 1 65 0 1
#> 23 16.92 1 61 0 0
#> 68 20.62 1 44 0 0
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 51 18.23 1 83 0 1
#> 117 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 100 16.07 1 60 0 0
#> 168 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 51.1 18.23 1 83 0 1
#> 5 16.43 1 51 0 1
#> 57.1 14.46 1 45 0 1
#> 26.1 15.77 1 49 0 1
#> 157 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 24 23.89 1 38 0 0
#> 139 21.49 1 63 1 0
#> 194 22.40 1 38 0 1
#> 105 19.75 1 60 0 0
#> 69.1 23.23 1 25 0 1
#> 134 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 41 18.02 1 40 1 0
#> 106 16.67 1 49 1 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 125 15.65 1 67 1 0
#> 100.1 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 81.1 14.06 1 34 0 0
#> 32 20.90 1 37 1 0
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 155.1 13.08 1 26 0 0
#> 85 16.44 1 36 0 0
#> 36 21.19 1 48 0 1
#> 36.1 21.19 1 48 0 1
#> 124 9.73 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 105.1 19.75 1 60 0 0
#> 111 17.45 1 47 0 1
#> 14 12.89 1 21 0 0
#> 179 18.63 1 42 0 0
#> 96 14.54 1 33 0 1
#> 16.2 8.71 1 71 0 1
#> 59 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 91 5.33 1 61 0 1
#> 164 23.60 1 76 0 1
#> 150 20.33 1 48 0 0
#> 117.1 17.46 1 26 0 1
#> 99 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 23.1 16.92 1 61 0 0
#> 86.1 23.81 1 58 0 1
#> 91.1 5.33 1 61 0 1
#> 164.1 23.60 1 76 0 1
#> 91.2 5.33 1 61 0 1
#> 184 17.77 1 38 0 0
#> 97.1 19.14 1 65 0 1
#> 40.1 18.00 1 28 1 0
#> 106.1 16.67 1 49 1 0
#> 86.2 23.81 1 58 0 1
#> 88 18.37 1 47 0 0
#> 23.2 16.92 1 61 0 0
#> 42 12.43 1 49 0 1
#> 79 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 168.1 23.72 1 70 0 0
#> 10 10.53 1 34 0 0
#> 25 6.32 1 34 1 0
#> 101 9.97 1 10 0 1
#> 81.2 14.06 1 34 0 0
#> 57.2 14.46 1 45 0 1
#> 70 7.38 1 30 1 0
#> 171 16.57 1 41 0 1
#> 190 20.81 1 42 1 0
#> 79.1 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 107 11.18 1 54 1 0
#> 93.1 10.33 1 52 0 1
#> 50.1 10.02 1 NA 1 0
#> 105.2 19.75 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 158 20.14 1 74 1 0
#> 166 19.98 1 48 0 0
#> 86.3 23.81 1 58 0 1
#> 93.2 10.33 1 52 0 1
#> 96.1 14.54 1 33 0 1
#> 59.1 10.16 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 5.1 16.43 1 51 0 1
#> 105.3 19.75 1 60 0 0
#> 81.3 14.06 1 34 0 0
#> 149 8.37 1 33 1 0
#> 157.1 15.10 1 47 0 0
#> 26.2 15.77 1 49 0 1
#> 106.2 16.67 1 49 1 0
#> 39.1 15.59 1 37 0 1
#> 26.3 15.77 1 49 0 1
#> 82 24.00 0 34 0 0
#> 137 24.00 0 45 1 0
#> 7 24.00 0 37 1 0
#> 20 24.00 0 46 1 0
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 67 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 71 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 173 24.00 0 19 0 1
#> 119 24.00 0 17 0 0
#> 65 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 94 24.00 0 51 0 1
#> 178 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 38 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 119.1 24.00 0 17 0 0
#> 47 24.00 0 38 0 1
#> 82.1 24.00 0 34 0 0
#> 28 24.00 0 67 1 0
#> 94.1 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 174 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 65.1 24.00 0 57 1 0
#> 173.1 24.00 0 19 0 1
#> 53 24.00 0 32 0 1
#> 121 24.00 0 57 1 0
#> 53.1 24.00 0 32 0 1
#> 20.1 24.00 0 46 1 0
#> 27.1 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 193 24.00 0 45 0 1
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 46.1 24.00 0 71 0 0
#> 65.2 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 83.1 24.00 0 6 0 0
#> 87.1 24.00 0 27 0 0
#> 142 24.00 0 53 0 0
#> 200.1 24.00 0 64 0 0
#> 193.1 24.00 0 45 0 1
#> 9 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 165 24.00 0 47 0 0
#> 20.2 24.00 0 46 1 0
#> 137.2 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 198 24.00 0 66 0 1
#> 21 24.00 0 47 0 0
#> 160.1 24.00 0 31 1 0
#> 44 24.00 0 56 0 0
#> 21.1 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 54 24.00 0 53 1 0
#> 71.1 24.00 0 51 0 0
#> 174.1 24.00 0 49 1 0
#> 152 24.00 0 36 0 1
#> 103 24.00 0 56 1 0
#> 35 24.00 0 51 0 0
#> 121.1 24.00 0 57 1 0
#> 121.2 24.00 0 57 1 0
#> 83.2 24.00 0 6 0 0
#> 147 24.00 0 76 1 0
#> 94.2 24.00 0 51 0 1
#> 20.3 24.00 0 46 1 0
#> 148 24.00 0 61 1 0
#> 182.1 24.00 0 35 0 0
#> 172 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.639 NA NA NA
#> 2 age, Cure model 0.0128 NA NA NA
#> 3 grade_ii, Cure model -0.338 NA NA NA
#> 4 grade_iii, Cure model 1.09 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00920 NA NA NA
#> 2 grade_ii, Survival model 0.311 NA NA NA
#> 3 grade_iii, Survival model 0.172 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63852 0.01279 -0.33761 1.09078
#>
#> Degrees of Freedom: 194 Total (i.e. Null); 191 Residual
#> Null Deviance: 268.5
#> Residual Deviance: 250.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.63852430 0.01278549 -0.33761059 1.09078195
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009198519 0.311090196 0.172129053
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.329042130 0.637951848 0.891519117 0.891519117 0.488130977 0.738839903
#> [7] 0.263986375 0.184356646 0.338615718 0.116259743 0.227381514 0.879586675
#> [13] 0.236385342 0.300958112 0.820476012 0.467382996 0.022044534 0.605192291
#> [19] 0.050549923 0.236385342 0.426810183 0.605192291 0.488130977 0.561720637
#> [25] 0.062893628 0.002057623 0.075977466 0.069385223 0.153239503 0.050549923
#> [31] 0.282240386 0.540324717 0.254660057 0.367557544 0.044050718 0.008499197
#> [37] 0.529585264 0.467382996 0.693369486 0.637951848 0.102244055 0.682057938
#> [43] 0.773586108 0.693369486 0.406844855 0.082707460 0.082707460 0.406844855
#> [49] 0.153239503 0.319545146 0.715963629 0.201148499 0.583406558 0.891519117
#> [55] 0.761975186 0.963703007 0.032272316 0.123428199 0.300958112 0.082707460
#> [61] 0.123428199 0.338615718 0.008499197 0.963703007 0.032272316 0.963703007
#> [67] 0.291554931 0.184356646 0.263986375 0.367557544 0.008499197 0.209846282
#> [73] 0.338615718 0.750385864 0.447018539 0.727383171 0.022044534 0.808690163
#> [79] 0.951597713 0.867661764 0.637951848 0.605192291 0.939492676 0.396800510
#> [85] 0.109235533 0.447018539 0.855723163 0.796950267 0.785253464 0.820476012
#> [91] 0.153239503 0.209846282 0.137933913 0.145514854 0.008499197 0.820476012
#> [97] 0.583406558 0.002057623 0.426810183 0.153239503 0.637951848 0.927382062
#> [103] 0.561720637 0.488130977 0.367557544 0.540324717 0.488130977 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 45 81 16 16.1 26 177 40 97 23 68 108 187 51
#> 17.42 14.06 8.71 8.71 15.77 12.53 18.00 19.14 16.92 20.62 18.29 9.92 18.23
#> 117 93 100 168 57 69 51.1 5 57.1 26.1 157 63 24
#> 17.46 10.33 16.07 23.72 14.46 23.23 18.23 16.43 14.46 15.77 15.10 22.77 23.89
#> 139 194 105 69.1 134 39 41 106 129 86 125 100.1 155
#> 21.49 22.40 19.75 23.23 17.81 15.59 18.02 16.67 23.41 23.81 15.65 16.07 13.08
#> 81.1 32 60 43 155.1 85 36 36.1 192 105.1 111 14 179
#> 14.06 20.90 13.15 12.10 13.08 16.44 21.19 21.19 16.44 19.75 17.45 12.89 18.63
#> 96 16.2 49 91 164 150 117.1 99 150.1 23.1 86.1 91.1 164.1
#> 14.54 8.71 12.19 5.33 23.60 20.33 17.46 21.19 20.33 16.92 23.81 5.33 23.60
#> 91.2 184 97.1 40.1 106.1 86.2 88 23.2 42 79 140 168.1 10
#> 5.33 17.77 19.14 18.00 16.67 23.81 18.37 16.92 12.43 16.23 12.68 23.72 10.53
#> 25 101 81.2 57.2 70 171 190 79.1 61 159 107 93.1 105.2
#> 6.32 9.97 14.06 14.46 7.38 16.57 20.81 16.23 10.12 10.55 11.18 10.33 19.75
#> 88.1 158 166 86.3 93.2 96.1 24.1 5.1 105.3 81.3 149 157.1 26.2
#> 18.37 20.14 19.98 23.81 10.33 14.54 23.89 16.43 19.75 14.06 8.37 15.10 15.77
#> 106.2 39.1 26.3 82 137 7 20 84 102 67 200 71 27
#> 16.67 15.59 15.77 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 46 98 173 119 65 162 138 34 34.1 94 178 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 38 137.1 83 119.1 47 82.1 28 94.1 182 174 87 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 53 121 53.1 20.1 27.1 176 22 193 186 163 109 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 118 98.1 83.1 87.1 142 200.1 193.1 9 144 160 131 19
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 20.2 137.2 146 33 198 21 160.1 44 21.1 132 54 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 152 103 35 121.1 121.2 83.2 147 94.2 20.3 148 182.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[16]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01587667 0.74536263 0.32393085
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.511488943 0.007000945 0.166976163
#> grade_iii, Cure model
#> 0.819345224
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 25 6.32 1 34 1 0
#> 139 21.49 1 63 1 0
#> 169 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 66 22.13 1 53 0 0
#> 192 16.44 1 31 1 0
#> 128 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 157 15.10 1 47 0 0
#> 89.1 11.44 1 NA 0 0
#> 23 16.92 1 61 0 0
#> 29 15.45 1 68 1 0
#> 91 5.33 1 61 0 1
#> 68 20.62 1 44 0 0
#> 145 10.07 1 65 1 0
#> 136 21.83 1 43 0 1
#> 169.1 22.41 1 46 0 0
#> 4 17.64 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 68.1 20.62 1 44 0 0
#> 159 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 155 13.08 1 26 0 0
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 134 17.81 1 47 1 0
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 42.1 12.43 1 49 0 1
#> 168 23.72 1 70 0 0
#> 123 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 18 15.21 1 49 1 0
#> 41 18.02 1 40 1 0
#> 114 13.68 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 184 17.77 1 38 0 0
#> 45 17.42 1 54 0 1
#> 86 23.81 1 58 0 1
#> 101.1 9.97 1 10 0 1
#> 59 10.16 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 15.1 22.68 1 48 0 0
#> 51 18.23 1 83 0 1
#> 39 15.59 1 37 0 1
#> 49 12.19 1 48 1 0
#> 170 19.54 1 43 0 1
#> 13 14.34 1 54 0 1
#> 43 12.10 1 61 0 1
#> 171.1 16.57 1 41 0 1
#> 96 14.54 1 33 0 1
#> 139.1 21.49 1 63 1 0
#> 114.1 13.68 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 59.1 10.16 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 124 9.73 1 NA 1 0
#> 189 10.51 1 NA 1 0
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 106 16.67 1 49 1 0
#> 59.2 10.16 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 133.1 14.65 1 57 0 0
#> 10 10.53 1 34 0 0
#> 168.1 23.72 1 70 0 0
#> 180.1 14.82 1 37 0 0
#> 113 22.86 1 34 0 0
#> 13.1 14.34 1 54 0 1
#> 177.1 12.53 1 75 0 0
#> 128.1 20.35 1 35 0 1
#> 41.1 18.02 1 40 1 0
#> 170.1 19.54 1 43 0 1
#> 114.2 13.68 1 NA 0 0
#> 41.2 18.02 1 40 1 0
#> 79 16.23 1 54 1 0
#> 171.2 16.57 1 41 0 1
#> 6 15.64 1 39 0 0
#> 77 7.27 1 67 0 1
#> 166 19.98 1 48 0 0
#> 192.1 16.44 1 31 1 0
#> 100 16.07 1 60 0 0
#> 159.1 10.55 1 50 0 1
#> 190 20.81 1 42 1 0
#> 167 15.55 1 56 1 0
#> 70.2 7.38 1 30 1 0
#> 32 20.90 1 37 1 0
#> 60 13.15 1 38 1 0
#> 51.1 18.23 1 83 0 1
#> 170.2 19.54 1 43 0 1
#> 133.2 14.65 1 57 0 0
#> 86.1 23.81 1 58 0 1
#> 153 21.33 1 55 1 0
#> 124.1 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 90 20.94 1 50 0 1
#> 194 22.40 1 38 0 1
#> 42.2 12.43 1 49 0 1
#> 145.1 10.07 1 65 1 0
#> 25.1 6.32 1 34 1 0
#> 187 9.92 1 39 1 0
#> 154.1 12.63 1 20 1 0
#> 51.2 18.23 1 83 0 1
#> 51.3 18.23 1 83 0 1
#> 150.1 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 173 24.00 0 19 0 1
#> 54 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 20 24.00 0 46 1 0
#> 38 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 185.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 176 24.00 0 43 0 1
#> 67.1 24.00 0 25 0 0
#> 102 24.00 0 49 0 0
#> 120 24.00 0 68 0 1
#> 109 24.00 0 48 0 0
#> 193.1 24.00 0 45 0 1
#> 21 24.00 0 47 0 0
#> 54.1 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 73 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 156 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 19 24.00 0 57 0 1
#> 64 24.00 0 43 0 0
#> 44.1 24.00 0 56 0 0
#> 122 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 172 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 104 24.00 0 50 1 0
#> 137.1 24.00 0 45 1 0
#> 38.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 38.2 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 33 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 31.1 24.00 0 36 0 1
#> 131 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 137.2 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 143.1 24.00 0 51 0 0
#> 73.1 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 20.1 24.00 0 46 1 0
#> 146 24.00 0 63 1 0
#> 9 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 47 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 122.1 24.00 0 66 0 0
#> 146.2 24.00 0 63 1 0
#> 200.1 24.00 0 64 0 0
#> 120.1 24.00 0 68 0 1
#> 98.1 24.00 0 34 1 0
#> 198 24.00 0 66 0 1
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 156.1 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 48 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 173.1 24.00 0 19 0 1
#> 173.2 24.00 0 19 0 1
#> 102.1 24.00 0 49 0 0
#> 87 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 82.1 24.00 0 34 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.511 NA NA NA
#> 2 age, Cure model 0.00700 NA NA NA
#> 3 grade_ii, Cure model 0.167 NA NA NA
#> 4 grade_iii, Cure model 0.819 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0159 NA NA NA
#> 2 grade_ii, Survival model 0.745 NA NA NA
#> 3 grade_iii, Survival model 0.324 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.511489 0.007001 0.166976 0.819345
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.511488943 0.007000945 0.166976163 0.819345224
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01587667 0.74536263 0.32393085
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9589571960 0.0396192131 0.0142927998 0.8354158444 0.2639848291
#> [6] 0.3059785977 0.0279874944 0.3488774355 0.1056159770 0.9046363668
#> [11] 0.4844563237 0.2846531354 0.4608960869 0.9861946888 0.0913943693
#> [16] 0.8077376047 0.0336510727 0.0142927998 0.5204906698 0.0913943693
#> [21] 0.7666538163 0.7000424050 0.6222567082 0.4963938623 0.5704920189
#> [26] 0.8767693294 0.2440511546 0.0577888972 0.1690168227 0.7000424050
#> [31] 0.0016247107 0.6353871063 0.0077613683 0.3488774355 0.4726714904
#> [36] 0.2156008764 0.4145421258 0.2539293770 0.2742384803 0.0002641659
#> [41] 0.8354158444 0.6739306147 0.0077613683 0.1779702331 0.4375556339
#> [46] 0.7396439143 0.1442226858 0.5833400633 0.7530913348 0.3059785977
#> [51] 0.5577368519 0.0396192131 0.8907298573 0.1202475774 0.3920357876
#> [56] 0.6485045299 0.2953096731 0.9046363668 0.5204906698 0.7938971171
#> [61] 0.0016247107 0.4963938623 0.0050641685 0.5833400633 0.6739306147
#> [66] 0.1056159770 0.2156008764 0.1442226858 0.2156008764 0.3809841252
#> [71] 0.3059785977 0.4259771355 0.9451502363 0.1358957971 0.3488774355
#> [76] 0.4031924967 0.7666538163 0.0845435749 0.4492055577 0.9046363668
#> [81] 0.0776474543 0.6092193573 0.1779702331 0.1442226858 0.5204906698
#> [86] 0.0002641659 0.0514136764 0.3377802504 0.0706454319 0.0229098513
#> [91] 0.7000424050 0.8077376047 0.9589571960 0.8629304724 0.6485045299
#> [96] 0.1779702331 0.1779702331 0.1202475774 0.0577888972 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 25 139 169 101 110 171 66 192 128 70 157 23 29
#> 6.32 21.49 22.41 9.97 17.56 16.57 22.13 16.44 20.35 7.38 15.10 16.92 15.45
#> 91 68 145 136 169.1 133 68.1 159 42 155 180 57 16
#> 5.33 20.62 10.07 21.83 22.41 14.65 20.62 10.55 12.43 13.08 14.82 14.46 8.71
#> 134 99 55 42.1 168 123 15 85 18 41 125 184 45
#> 17.81 21.19 19.34 12.43 23.72 13.00 22.68 16.44 15.21 18.02 15.65 17.77 17.42
#> 86 101.1 177 15.1 51 39 49 170 13 43 171.1 96 139.1
#> 23.81 9.97 12.53 22.68 18.23 15.59 12.19 19.54 14.34 12.10 16.57 14.54 21.49
#> 149 150 188 154 106 70.1 133.1 10 168.1 180.1 113 13.1 177.1
#> 8.37 20.33 16.16 12.63 16.67 7.38 14.65 10.53 23.72 14.82 22.86 14.34 12.53
#> 128.1 41.1 170.1 41.2 79 171.2 6 77 166 192.1 100 159.1 190
#> 20.35 18.02 19.54 18.02 16.23 16.57 15.64 7.27 19.98 16.44 16.07 10.55 20.81
#> 167 70.2 32 60 51.1 170.2 133.2 86.1 153 130 90 194 42.2
#> 15.55 7.38 20.90 13.15 18.23 19.54 14.65 23.81 21.33 16.47 20.94 22.40 12.43
#> 145.1 25.1 187 154.1 51.2 51.3 150.1 36 173 54 118 152 191
#> 10.07 6.32 9.92 12.63 18.23 18.23 20.33 21.19 24.00 24.00 24.00 24.00 24.00
#> 132 67 71 20 38 62 185 193 185.1 82 143 11 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 67.1 102 120 109 193.1 21 54.1 27 53 141 31 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 44 19 64 44.1 122 12 172 137 104 137.1 38.1 28
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38.2 72 33 75 160 31.1 131 196 137.2 151 143.1 165 27.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 17 20.1 146 9 98 47 146.1 122.1 146.2 200.1 120.1 98.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 80 94 156.1 3 62.1 48 131.1 142 173.1 173.2 102.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 161 82.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[17]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01763506 0.87472099 0.80248382
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.139952023 0.007015773 -0.392636763
#> grade_iii, Cure model
#> 0.412303108
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 77 7.27 1 67 0 1
#> 18 15.21 1 49 1 0
#> 170 19.54 1 43 0 1
#> 123 13.00 1 44 1 0
#> 189 10.51 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 127 3.53 1 62 0 1
#> 106 16.67 1 49 1 0
#> 70 7.38 1 30 1 0
#> 14 12.89 1 21 0 0
#> 5 16.43 1 51 0 1
#> 129 23.41 1 53 1 0
#> 167 15.55 1 56 1 0
#> 91 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 55 19.34 1 69 0 1
#> 155 13.08 1 26 0 0
#> 113 22.86 1 34 0 0
#> 154 12.63 1 20 1 0
#> 153 21.33 1 55 1 0
#> 88 18.37 1 47 0 0
#> 170.1 19.54 1 43 0 1
#> 171 16.57 1 41 0 1
#> 117 17.46 1 26 0 1
#> 90 20.94 1 50 0 1
#> 24 23.89 1 38 0 0
#> 26 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 113.1 22.86 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 136 21.83 1 43 0 1
#> 5.1 16.43 1 51 0 1
#> 100 16.07 1 60 0 0
#> 134 17.81 1 47 1 0
#> 51 18.23 1 83 0 1
#> 16 8.71 1 71 0 1
#> 180 14.82 1 37 0 0
#> 70.1 7.38 1 30 1 0
#> 183 9.24 1 67 1 0
#> 96 14.54 1 33 0 1
#> 154.1 12.63 1 20 1 0
#> 153.1 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 140 12.68 1 59 1 0
#> 24.1 23.89 1 38 0 0
#> 100.1 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 8 18.43 1 32 0 0
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 42 12.43 1 49 0 1
#> 85.1 16.44 1 36 0 0
#> 113.2 22.86 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 55.1 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 88.2 18.37 1 47 0 0
#> 81 14.06 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 117.1 17.46 1 26 0 1
#> 51.1 18.23 1 83 0 1
#> 66 22.13 1 53 0 0
#> 14.1 12.89 1 21 0 0
#> 93 10.33 1 52 0 1
#> 166 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 25 6.32 1 34 1 0
#> 15 22.68 1 48 0 0
#> 42.1 12.43 1 49 0 1
#> 133 14.65 1 57 0 0
#> 70.2 7.38 1 30 1 0
#> 39 15.59 1 37 0 1
#> 197.1 21.60 1 69 1 0
#> 192 16.44 1 31 1 0
#> 168 23.72 1 70 0 0
#> 99.1 21.19 1 38 0 1
#> 6 15.64 1 39 0 0
#> 8.2 18.43 1 32 0 0
#> 89 11.44 1 NA 0 0
#> 76 19.22 1 54 0 1
#> 39.1 15.59 1 37 0 1
#> 125 15.65 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 180.1 14.82 1 37 0 0
#> 14.2 12.89 1 21 0 0
#> 180.2 14.82 1 37 0 0
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 91.1 5.33 1 61 0 1
#> 129.1 23.41 1 53 1 0
#> 127.1 3.53 1 62 0 1
#> 50 10.02 1 NA 1 0
#> 108 18.29 1 39 0 1
#> 187 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 197.2 21.60 1 69 1 0
#> 189.1 10.51 1 NA 1 0
#> 55.2 19.34 1 69 0 1
#> 150.1 20.33 1 48 0 0
#> 68 20.62 1 44 0 0
#> 113.3 22.86 1 34 0 0
#> 130 16.47 1 53 0 1
#> 105.1 19.75 1 60 0 0
#> 181 16.46 1 45 0 1
#> 167.1 15.55 1 56 1 0
#> 140.1 12.68 1 59 1 0
#> 162 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 62 24.00 0 71 0 0
#> 119 24.00 0 17 0 0
#> 148 24.00 0 61 1 0
#> 7 24.00 0 37 1 0
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 65 24.00 0 57 1 0
#> 65.1 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 186 24.00 0 45 1 0
#> 119.1 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 2 24.00 0 9 0 0
#> 112.1 24.00 0 61 0 0
#> 12.1 24.00 0 63 0 0
#> 54 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 65.2 24.00 0 57 1 0
#> 147 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 67 24.00 0 25 0 0
#> 104 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 104.1 24.00 0 50 1 0
#> 53.1 24.00 0 32 0 1
#> 1 24.00 0 23 1 0
#> 33 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 176 24.00 0 43 0 1
#> 27 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 104.2 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 104.3 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 152.1 24.00 0 36 0 1
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 22 24.00 0 52 1 0
#> 80 24.00 0 41 0 0
#> 98 24.00 0 34 1 0
#> 98.1 24.00 0 34 1 0
#> 31 24.00 0 36 0 1
#> 72.1 24.00 0 40 0 1
#> 44 24.00 0 56 0 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 132.1 24.00 0 55 0 0
#> 138.1 24.00 0 44 1 0
#> 87.1 24.00 0 27 0 0
#> 20 24.00 0 46 1 0
#> 104.4 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 27.1 24.00 0 63 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 160 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 48 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 19.1 24.00 0 57 0 1
#> 11 24.00 0 42 0 1
#> 200.1 24.00 0 64 0 0
#> 176.2 24.00 0 43 0 1
#> 162.1 24.00 0 51 0 0
#> 48.1 24.00 0 31 1 0
#> 87.2 24.00 0 27 0 0
#> 82 24.00 0 34 0 0
#> 65.3 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 132.2 24.00 0 55 0 0
#> 54.1 24.00 0 53 1 0
#> 11.1 24.00 0 42 0 1
#> 122 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 62.1 24.00 0 71 0 0
#> 121.1 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.140 NA NA NA
#> 2 age, Cure model 0.00702 NA NA NA
#> 3 grade_ii, Cure model -0.393 NA NA NA
#> 4 grade_iii, Cure model 0.412 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0176 NA NA NA
#> 2 grade_ii, Survival model 0.875 NA NA NA
#> 3 grade_iii, Survival model 0.802 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.139952 0.007016 -0.392637 0.412303
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 260.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.139952023 0.007015773 -0.392636763 0.412303108
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01763506 0.87472099 0.80248382
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8456784137 0.9287386931 0.5861703678 0.1733747396 0.6913065751
#> [6] 0.0433691386 0.9761671604 0.3778520343 0.8936501244 0.7032001977
#> [11] 0.4524526978 0.0125947121 0.5635956448 0.9524803082 0.8100604533
#> [16] 0.1903574253 0.6793916758 0.0201623782 0.7628998689 0.0835736009
#> [21] 0.2725445100 0.1733747396 0.3885598548 0.3567335910 0.1180664103
#> [26] 0.0003412879 0.5071166781 0.0024096153 0.0201623782 0.6675531372
#> [31] 0.0566007919 0.4524526978 0.4848959493 0.3349190570 0.3135905727
#> [36] 0.8815994903 0.5975661941 0.8936501244 0.8696082129 0.6438767551
#> [41] 0.7628998689 0.0835736009 0.1563179988 0.2725445100 0.7388313821
#> [46] 0.0003412879 0.4848959493 0.4739856251 0.2438143138 0.4206789106
#> [51] 0.1327174034 0.7864590062 0.4206789106 0.0201623782 0.8100604533
#> [56] 0.1903574253 0.0978193642 0.2725445100 0.6556667506 0.2438143138
#> [61] 0.3567335910 0.3135905727 0.0497178366 0.7032001977 0.8337365980
#> [66] 0.1481432979 0.0634472161 0.9406332216 0.0374986089 0.7864590062
#> [71] 0.6320332592 0.8936501244 0.5411171066 0.0634472161 0.4206789106
#> [76] 0.0047106464 0.0978193642 0.5296810078 0.2438143138 0.2250576495
#> [81] 0.5411171066 0.5183663990 0.2343377938 0.3457423005 0.5975661941
#> [86] 0.7032001977 0.5975661941 0.0082545242 0.0978193642 0.9524803082
#> [91] 0.0125947121 0.9761671604 0.3030903856 0.8576604684 0.1903574253
#> [96] 0.0634472161 0.1903574253 0.1327174034 0.1252763091 0.0201623782
#> [101] 0.3992433512 0.1563179988 0.4099623761 0.5635956448 0.7388313821
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 145 77 18 170 123 169 127 106 70 14 5 129 167
#> 10.07 7.27 15.21 19.54 13.00 22.41 3.53 16.67 7.38 12.89 16.43 23.41 15.55
#> 91 52 55 155 113 154 153 88 170.1 171 117 90 24
#> 5.33 10.42 19.34 13.08 22.86 12.63 21.33 18.37 19.54 16.57 17.46 20.94 23.89
#> 26 78 113.1 60 136 5.1 100 134 51 16 180 70.1 183
#> 15.77 23.88 22.86 13.15 21.83 16.43 16.07 17.81 18.23 8.71 14.82 7.38 9.24
#> 96 154.1 153.1 105 88.1 140 24.1 100.1 79 8 85 150 42
#> 14.54 12.63 21.33 19.75 18.37 12.68 23.89 16.07 16.23 18.43 16.44 20.33 12.43
#> 85.1 113.2 52.1 55.1 99 88.2 81 8.1 117.1 51.1 66 14.1 93
#> 16.44 22.86 10.42 19.34 21.19 18.37 14.06 18.43 17.46 18.23 22.13 12.89 10.33
#> 166 197 25 15 42.1 133 70.2 39 197.1 192 168 99.1 6
#> 19.98 21.60 6.32 22.68 12.43 14.65 7.38 15.59 21.60 16.44 23.72 21.19 15.64
#> 8.2 76 39.1 125 179 184 180.1 14.2 180.2 164 36 91.1 129.1
#> 18.43 19.22 15.59 15.65 18.63 17.77 14.82 12.89 14.82 23.60 21.19 5.33 23.41
#> 127.1 108 187 58 197.2 55.2 150.1 68 113.3 130 105.1 181 167.1
#> 3.53 18.29 9.92 19.34 21.60 19.34 20.33 20.62 22.86 16.47 19.75 16.46 15.55
#> 140.1 162 19 53 62 119 148 7 132 137 112 65 65.1
#> 12.68 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 12 186 119.1 87 2 112.1 12.1 54 200 65.2 147 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 104 103 104.1 53.1 1 33 152 176 27 138 104.2 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 38 33.1 104.3 9 152.1 182 84 22 80 98 98.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 44 131 120 132.1 138.1 87.1 20 104.4 176.1 27.1 34 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 185 120.1 48 144 19.1 11 200.1 176.2 162.1 48.1 87.2 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.3 196 83 132.2 54.1 11.1 122 47 143 62.1 121.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[18]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003551843 0.408664005 -0.251621659
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.550225302 0.009836803 0.154515846
#> grade_iii, Cure model
#> 0.747454418
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 113 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 171 16.57 1 41 0 1
#> 57 14.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 58 19.34 1 39 0 0
#> 85 16.44 1 36 0 0
#> 39 15.59 1 37 0 1
#> 68 20.62 1 44 0 0
#> 197 21.60 1 69 1 0
#> 77 7.27 1 67 0 1
#> 85.1 16.44 1 36 0 0
#> 136 21.83 1 43 0 1
#> 78 23.88 1 43 0 0
#> 157 15.10 1 47 0 0
#> 133 14.65 1 57 0 0
#> 29 15.45 1 68 1 0
#> 37 12.52 1 57 1 0
#> 37.1 12.52 1 57 1 0
#> 78.1 23.88 1 43 0 0
#> 8 18.43 1 32 0 0
#> 192 16.44 1 31 1 0
#> 157.1 15.10 1 47 0 0
#> 177 12.53 1 75 0 0
#> 96 14.54 1 33 0 1
#> 70 7.38 1 30 1 0
#> 36 21.19 1 48 0 1
#> 56 12.21 1 60 0 0
#> 136.1 21.83 1 43 0 1
#> 23 16.92 1 61 0 0
#> 30 17.43 1 78 0 0
#> 179 18.63 1 42 0 0
#> 66 22.13 1 53 0 0
#> 8.1 18.43 1 32 0 0
#> 14 12.89 1 21 0 0
#> 37.2 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 55 19.34 1 69 0 1
#> 66.1 22.13 1 53 0 0
#> 61 10.12 1 36 0 1
#> 189 10.51 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 63 22.77 1 31 1 0
#> 68.1 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 60 13.15 1 38 1 0
#> 125 15.65 1 67 1 0
#> 153 21.33 1 55 1 0
#> 29.1 15.45 1 68 1 0
#> 189.1 10.51 1 NA 1 0
#> 96.1 14.54 1 33 0 1
#> 39.1 15.59 1 37 0 1
#> 150 20.33 1 48 0 0
#> 5 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 157.2 15.10 1 47 0 0
#> 170 19.54 1 43 0 1
#> 69 23.23 1 25 0 1
#> 139 21.49 1 63 1 0
#> 42 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 183 9.24 1 67 1 0
#> 60.1 13.15 1 38 1 0
#> 42.1 12.43 1 49 0 1
#> 154 12.63 1 20 1 0
#> 159 10.55 1 50 0 1
#> 59 10.16 1 NA 1 0
#> 166 19.98 1 48 0 0
#> 63.1 22.77 1 31 1 0
#> 183.1 9.24 1 67 1 0
#> 113.1 22.86 1 34 0 0
#> 41 18.02 1 40 1 0
#> 69.1 23.23 1 25 0 1
#> 105 19.75 1 60 0 0
#> 133.1 14.65 1 57 0 0
#> 154.1 12.63 1 20 1 0
#> 164.1 23.60 1 76 0 1
#> 86 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 99.1 21.19 1 38 0 1
#> 56.1 12.21 1 60 0 0
#> 90 20.94 1 50 0 1
#> 77.1 7.27 1 67 0 1
#> 133.2 14.65 1 57 0 0
#> 184 17.77 1 38 0 0
#> 180 14.82 1 37 0 0
#> 108 18.29 1 39 0 1
#> 29.2 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 164.2 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 136.2 21.83 1 43 0 1
#> 164.3 23.60 1 76 0 1
#> 88 18.37 1 47 0 0
#> 139.2 21.49 1 63 1 0
#> 180.1 14.82 1 37 0 0
#> 139.3 21.49 1 63 1 0
#> 197.1 21.60 1 69 1 0
#> 37.3 12.52 1 57 1 0
#> 150.1 20.33 1 48 0 0
#> 59.1 10.16 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 10 10.53 1 34 0 0
#> 164.4 23.60 1 76 0 1
#> 181 16.46 1 45 0 1
#> 86.1 23.81 1 58 0 1
#> 177.1 12.53 1 75 0 0
#> 195 11.76 1 NA 1 0
#> 37.4 12.52 1 57 1 0
#> 69.2 23.23 1 25 0 1
#> 118 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 147.1 24.00 0 76 1 0
#> 191 24.00 0 60 0 1
#> 27 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 191.1 24.00 0 60 0 1
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 3.1 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 3.2 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#> 28 24.00 0 67 1 0
#> 200 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 160 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 74.1 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 163 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 163.1 24.00 0 66 0 0
#> 196 24.00 0 19 0 0
#> 102.1 24.00 0 49 0 0
#> 162 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 120 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 131 24.00 0 66 0 0
#> 126 24.00 0 48 0 0
#> 143 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 64 24.00 0 43 0 0
#> 87 24.00 0 27 0 0
#> 72.1 24.00 0 40 0 1
#> 71 24.00 0 51 0 0
#> 200.1 24.00 0 64 0 0
#> 75 24.00 0 21 1 0
#> 141 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 151.1 24.00 0 42 0 0
#> 173 24.00 0 19 0 1
#> 12.1 24.00 0 63 0 0
#> 191.2 24.00 0 60 0 1
#> 72.2 24.00 0 40 0 1
#> 33.1 24.00 0 53 0 0
#> 126.1 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 54 24.00 0 53 1 0
#> 84.1 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 84.2 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 143.1 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 178.1 24.00 0 52 1 0
#> 21.1 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 103.1 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 87.1 24.00 0 27 0 0
#> 141.1 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 156 24.00 0 50 1 0
#> 161.1 24.00 0 45 0 0
#> 74.2 24.00 0 43 0 1
#> 126.2 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 121.1 24.00 0 57 1 0
#> 131.1 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 161.2 24.00 0 45 0 0
#> 12.2 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.550 NA NA NA
#> 2 age, Cure model 0.00984 NA NA NA
#> 3 grade_ii, Cure model 0.155 NA NA NA
#> 4 grade_iii, Cure model 0.747 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00355 NA NA NA
#> 2 grade_ii, Survival model 0.409 NA NA NA
#> 3 grade_iii, Survival model -0.252 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.550225 0.009837 0.154516 0.747454
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 261.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.550225302 0.009836803 0.154515846 0.747454418
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003551843 0.408664005 -0.251621659
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.079445333 0.742446218 0.455899790 0.700570392 0.895586735 0.327997741
#> [7] 0.476296101 0.547260227 0.262972204 0.167360103 0.979077979 0.476296101
#> [13] 0.140387289 0.003773719 0.597934933 0.648870563 0.567759465 0.794113713
#> [19] 0.794113713 0.003773719 0.366700188 0.476296101 0.597934933 0.773444226
#> [25] 0.679677679 0.968647239 0.227553310 0.864568657 0.140387289 0.435949335
#> [31] 0.425947577 0.356880139 0.114124731 0.366700188 0.731956754 0.794113713
#> [37] 0.347097409 0.327997741 0.114124731 0.937304409 0.435949335 0.097316381
#> [43] 0.262972204 0.885176536 0.711149430 0.537035860 0.218794278 0.567759465
#> [49] 0.679677679 0.547260227 0.281194158 0.506280929 0.227553310 0.597934933
#> [55] 0.318451756 0.054816793 0.185508999 0.844054647 0.023657879 0.947819408
#> [61] 0.711149430 0.844054647 0.752903137 0.905967714 0.299603462 0.097316381
#> [67] 0.947819408 0.079445333 0.406087032 0.054816793 0.309000017 0.648870563
#> [73] 0.752903137 0.023657879 0.012098366 0.926826531 0.185508999 0.227553310
#> [79] 0.864568657 0.253791619 0.979077979 0.648870563 0.416002336 0.628346644
#> [85] 0.396097227 0.567759465 0.526775142 0.023657879 0.131372904 0.140387289
#> [91] 0.023657879 0.386188162 0.185508999 0.628346644 0.185508999 0.167360103
#> [97] 0.794113713 0.281194158 0.516552645 0.916390371 0.023657879 0.466060307
#> [103] 0.012098366 0.773444226 0.794113713 0.054816793 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 113 140 171 57 107 58 85 39 68 197 77 85.1 136
#> 22.86 12.68 16.57 14.46 11.18 19.34 16.44 15.59 20.62 21.60 7.27 16.44 21.83
#> 78 157 133 29 37 37.1 78.1 8 192 157.1 177 96 70
#> 23.88 15.10 14.65 15.45 12.52 12.52 23.88 18.43 16.44 15.10 12.53 14.54 7.38
#> 36 56 136.1 23 30 179 66 8.1 14 37.2 76 55 66.1
#> 21.19 12.21 21.83 16.92 17.43 18.63 22.13 18.43 12.89 12.52 19.22 19.34 22.13
#> 61 23.1 63 68.1 43 60 125 153 29.1 96.1 39.1 150 5
#> 10.12 16.92 22.77 20.62 12.10 13.15 15.65 21.33 15.45 14.54 15.59 20.33 16.43
#> 99 157.2 170 69 139 42 164 183 60.1 42.1 154 159 166
#> 21.19 15.10 19.54 23.23 21.49 12.43 23.60 9.24 13.15 12.43 12.63 10.55 19.98
#> 63.1 183.1 113.1 41 69.1 105 133.1 154.1 164.1 86 93 139.1 99.1
#> 22.77 9.24 22.86 18.02 23.23 19.75 14.65 12.63 23.60 23.81 10.33 21.49 21.19
#> 56.1 90 77.1 133.2 184 180 108 29.2 100 164.2 175 136.2 164.3
#> 12.21 20.94 7.27 14.65 17.77 14.82 18.29 15.45 16.07 23.60 21.91 21.83 23.60
#> 88 139.2 180.1 139.3 197.1 37.3 150.1 79 10 164.4 181 86.1 177.1
#> 18.37 21.49 14.82 21.49 21.60 12.52 20.33 16.23 10.53 23.60 16.46 23.81 12.53
#> 37.4 69.2 118 74 3 147 147.1 191 27 152 138 161 191.1
#> 12.52 23.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 102 80 3.1 104 3.2 21 72 178 28 200 84 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 74.1 174 163 33 163.1 196 102.1 162 103 120 119 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 143 137 94 172 151 64 87 72.1 71 200.1 75 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 7 11 151.1 173 12.1 191.2 72.2 33.1 126.1 82 54 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 84.2 44 143.1 146 178.1 21.1 46 103.1 144 87.1 141.1 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 121 156 161.1 74.2 126.2 142 121.1 131.1 34 161.2 12.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[19]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.009458748 0.509878786 0.266804593
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.2629980 0.0277954 -0.1038753
#> grade_iii, Cure model
#> 0.6678219
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 37 12.52 1 57 1 0
#> 164 23.60 1 76 0 1
#> 188 16.16 1 46 0 1
#> 197 21.60 1 69 1 0
#> 127 3.53 1 62 0 1
#> 166 19.98 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 55 19.34 1 69 0 1
#> 37.1 12.52 1 57 1 0
#> 195 11.76 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 155.1 13.08 1 26 0 0
#> 36 21.19 1 48 0 1
#> 86 23.81 1 58 0 1
#> 26 15.77 1 49 0 1
#> 188.2 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 93 10.33 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 97.1 19.14 1 65 0 1
#> 58 19.34 1 39 0 0
#> 184 17.77 1 38 0 0
#> 170 19.54 1 43 0 1
#> 158 20.14 1 74 1 0
#> 24 23.89 1 38 0 0
#> 68 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 175 21.91 1 43 0 0
#> 55.1 19.34 1 69 0 1
#> 89 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 188.3 16.16 1 46 0 1
#> 188.4 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 24.1 23.89 1 38 0 0
#> 187 9.92 1 39 1 0
#> 51 18.23 1 83 0 1
#> 117 17.46 1 26 0 1
#> 43 12.10 1 61 0 1
#> 175.1 21.91 1 43 0 0
#> 134 17.81 1 47 1 0
#> 56 12.21 1 60 0 0
#> 128 20.35 1 35 0 1
#> 41.1 18.02 1 40 1 0
#> 149 8.37 1 33 1 0
#> 170.1 19.54 1 43 0 1
#> 167 15.55 1 56 1 0
#> 179 18.63 1 42 0 0
#> 81 14.06 1 34 0 0
#> 58.1 19.34 1 39 0 0
#> 105.1 19.75 1 60 0 0
#> 97.2 19.14 1 65 0 1
#> 89.1 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 117.1 17.46 1 26 0 1
#> 175.2 21.91 1 43 0 0
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 45 17.42 1 54 0 1
#> 167.1 15.55 1 56 1 0
#> 166.1 19.98 1 48 0 0
#> 52 10.42 1 52 0 1
#> 81.1 14.06 1 34 0 0
#> 125 15.65 1 67 1 0
#> 81.2 14.06 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 32 20.90 1 37 1 0
#> 140 12.68 1 59 1 0
#> 125.1 15.65 1 67 1 0
#> 26.1 15.77 1 49 0 1
#> 105.2 19.75 1 60 0 0
#> 111 17.45 1 47 0 1
#> 58.2 19.34 1 39 0 0
#> 187.1 9.92 1 39 1 0
#> 58.3 19.34 1 39 0 0
#> 40 18.00 1 28 1 0
#> 197.1 21.60 1 69 1 0
#> 179.1 18.63 1 42 0 0
#> 29 15.45 1 68 1 0
#> 88 18.37 1 47 0 0
#> 39 15.59 1 37 0 1
#> 180 14.82 1 37 0 0
#> 150 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 39.1 15.59 1 37 0 1
#> 92 22.92 1 47 0 1
#> 108 18.29 1 39 0 1
#> 81.3 14.06 1 34 0 0
#> 26.2 15.77 1 49 0 1
#> 30 17.43 1 78 0 0
#> 86.1 23.81 1 58 0 1
#> 192 16.44 1 31 1 0
#> 81.4 14.06 1 34 0 0
#> 97.3 19.14 1 65 0 1
#> 169 22.41 1 46 0 0
#> 92.1 22.92 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 43.1 12.10 1 61 0 1
#> 37.2 12.52 1 57 1 0
#> 134.1 17.81 1 47 1 0
#> 42 12.43 1 49 0 1
#> 29.1 15.45 1 68 1 0
#> 124.1 9.73 1 NA 1 0
#> 177.1 12.53 1 75 0 0
#> 150.1 20.33 1 48 0 0
#> 153 21.33 1 55 1 0
#> 154 12.63 1 20 1 0
#> 115 24.00 0 NA 1 0
#> 163 24.00 0 66 0 0
#> 115.1 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 160 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 141 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 116.1 24.00 0 58 0 1
#> 193 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 82 24.00 0 34 0 0
#> 121.1 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 72 24.00 0 40 0 1
#> 33.1 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 80 24.00 0 41 0 0
#> 137 24.00 0 45 1 0
#> 163.1 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 20.1 24.00 0 46 1 0
#> 104 24.00 0 50 1 0
#> 160.1 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 20.2 24.00 0 46 1 0
#> 20.3 24.00 0 46 1 0
#> 163.2 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 33.2 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 12 24.00 0 63 0 0
#> 64 24.00 0 43 0 0
#> 186 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 146 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 44 24.00 0 56 0 0
#> 109.1 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 161 24.00 0 45 0 0
#> 161.1 24.00 0 45 0 0
#> 2 24.00 0 9 0 0
#> 65 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 193.1 24.00 0 45 0 1
#> 47.1 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 84 24.00 0 39 0 1
#> 83.1 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 119 24.00 0 17 0 0
#> 103 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 46 24.00 0 71 0 0
#> 138.1 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 54.1 24.00 0 53 1 0
#> 17 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 67 24.00 0 25 0 0
#> 7.1 24.00 0 37 1 0
#> 186.1 24.00 0 45 1 0
#> 72.1 24.00 0 40 0 1
#> 19.1 24.00 0 57 0 1
#> 17.1 24.00 0 38 0 1
#> 48.1 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 142.1 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 83.2 24.00 0 6 0 0
#> 142.2 24.00 0 53 0 0
#> 80.1 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.26 NA NA NA
#> 2 age, Cure model 0.0278 NA NA NA
#> 3 grade_ii, Cure model -0.104 NA NA NA
#> 4 grade_iii, Cure model 0.668 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00946 NA NA NA
#> 2 grade_ii, Survival model 0.510 NA NA NA
#> 3 grade_iii, Survival model 0.267 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2630 0.0278 -0.1039 0.6678
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 250.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2629980 0.0277954 -0.1038753 0.6678219
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.009458748 0.509878786 0.266804593
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.773722477 0.840683524 0.018937069 0.508257000 0.077563250 0.988493251
#> [7] 0.171257965 0.508257000 0.231862017 0.840683524 0.069993785 0.773722477
#> [13] 0.107865083 0.009512919 0.559156925 0.508257000 0.285093276 0.942615419
#> [19] 0.285093276 0.231862017 0.425329586 0.213970646 0.162984567 0.002270806
#> [25] 0.131219567 0.762605749 0.187981252 0.374373181 0.049906185 0.231862017
#> [31] 0.123503669 0.508257000 0.508257000 0.025115949 0.002270806 0.954158917
#> [37] 0.363928043 0.435644763 0.896837126 0.049906185 0.405095754 0.885453118
#> [43] 0.139093173 0.374373181 0.977023033 0.213970646 0.633119409 0.323236119
#> [49] 0.708494866 0.231862017 0.187981252 0.285093276 0.697563433 0.435644763
#> [55] 0.049906185 0.092335453 0.919613890 0.476806796 0.633119409 0.171257965
#> [61] 0.931100340 0.708494866 0.590590618 0.708494866 0.818259923 0.115730060
#> [67] 0.795934400 0.590590618 0.559156925 0.187981252 0.456010948 0.231862017
#> [73] 0.954158917 0.231862017 0.394814254 0.077563250 0.323236119 0.654427454
#> [79] 0.343306703 0.611825489 0.675822498 0.146994725 0.686657105 0.611825489
#> [85] 0.031289661 0.353602775 0.708494866 0.559156925 0.466348383 0.009512919
#> [91] 0.497812693 0.708494866 0.285093276 0.043147055 0.031289661 0.487315116
#> [97] 0.896837126 0.840683524 0.405095754 0.874132144 0.654427454 0.818259923
#> [103] 0.146994725 0.100097016 0.807126345 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 155 37 164 188 197 127 166 188.1 55 37.1 136 155.1 36
#> 13.08 12.52 23.60 16.16 21.60 3.53 19.98 16.16 19.34 12.52 21.83 13.08 21.19
#> 86 26 188.2 97 93 97.1 58 184 170 158 24 68 60
#> 23.81 15.77 16.16 19.14 10.33 19.14 19.34 17.77 19.54 20.14 23.89 20.62 13.15
#> 105 41 175 55.1 190 188.3 188.4 129 24.1 187 51 117 43
#> 19.75 18.02 21.91 19.34 20.81 16.16 16.16 23.41 23.89 9.92 18.23 17.46 12.10
#> 175.1 134 56 128 41.1 149 170.1 167 179 81 58.1 105.1 97.2
#> 21.91 17.81 12.21 20.35 18.02 8.37 19.54 15.55 18.63 14.06 19.34 19.75 19.14
#> 57 117.1 175.2 139 159 45 167.1 166.1 52 81.1 125 81.2 177
#> 14.46 17.46 21.91 21.49 10.55 17.42 15.55 19.98 10.42 14.06 15.65 14.06 12.53
#> 32 140 125.1 26.1 105.2 111 58.2 187.1 58.3 40 197.1 179.1 29
#> 20.90 12.68 15.65 15.77 19.75 17.45 19.34 9.92 19.34 18.00 21.60 18.63 15.45
#> 88 39 180 150 133 39.1 92 108 81.3 26.2 30 86.1 192
#> 18.37 15.59 14.82 20.33 14.65 15.59 22.92 18.29 14.06 15.77 17.43 23.81 16.44
#> 81.4 97.3 169 92.1 106 43.1 37.2 134.1 42 29.1 177.1 150.1 153
#> 14.06 19.14 22.41 22.92 16.67 12.10 12.52 17.81 12.43 15.45 12.53 20.33 21.33
#> 154 163 196 11 162 75 160 94 116 141 121 162.1 3
#> 12.63 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 116.1 193 20 172 54 132 82 121.1 138 33 72 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 80 137 163.1 109 20.1 104 160.1 47 104.1 20.2 20.3 163.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 33.2 87 12 64 186 137.1 146 19 44 109.1 21 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 2 65 144 193.1 47.1 147 84 83.1 9 142 119 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 53 46 138.1 94.1 54.1 17 35 7 67 7.1 186.1 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 17.1 48.1 71 142.1 22 83.2 142.2 80.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[20]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00381439 0.55129211 0.31773585
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.3694119 0.0048528 -0.1132853
#> grade_iii, Cure model
#> 1.2560246
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 50 10.02 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 5 16.43 1 51 0 1
#> 26 15.77 1 49 0 1
#> 110 17.56 1 65 0 1
#> 125 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 153 21.33 1 55 1 0
#> 36 21.19 1 48 0 1
#> 77 7.27 1 67 0 1
#> 125.1 15.65 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 49 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 90 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 5.1 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 127 3.53 1 62 0 1
#> 92 22.92 1 47 0 1
#> 130 16.47 1 53 0 1
#> 168 23.72 1 70 0 0
#> 8 18.43 1 32 0 0
#> 108 18.29 1 39 0 1
#> 101 9.97 1 10 0 1
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 107 11.18 1 54 1 0
#> 197 21.60 1 69 1 0
#> 199 19.81 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 79.1 16.23 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 8.1 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 6 15.64 1 39 0 0
#> 129 23.41 1 53 1 0
#> 14 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 184 17.77 1 38 0 0
#> 43 12.10 1 61 0 1
#> 60 13.15 1 38 1 0
#> 111 17.45 1 47 0 1
#> 24 23.89 1 38 0 0
#> 91 5.33 1 61 0 1
#> 39 15.59 1 37 0 1
#> 114 13.68 1 NA 0 0
#> 159.2 10.55 1 50 0 1
#> 52 10.42 1 52 0 1
#> 51 18.23 1 83 0 1
#> 164 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 24.1 23.89 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 8.2 18.43 1 32 0 0
#> 111.1 17.45 1 47 0 1
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 140 12.68 1 59 1 0
#> 134 17.81 1 47 1 0
#> 170 19.54 1 43 0 1
#> 56 12.21 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 158 20.14 1 74 1 0
#> 76 19.22 1 54 0 1
#> 96 14.54 1 33 0 1
#> 114.1 13.68 1 NA 0 0
#> 10 10.53 1 34 0 0
#> 81 14.06 1 34 0 0
#> 5.2 16.43 1 51 0 1
#> 13 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 55 19.34 1 69 0 1
#> 187 9.92 1 39 1 0
#> 5.3 16.43 1 51 0 1
#> 130.1 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 32.1 20.90 1 37 1 0
#> 180 14.82 1 37 0 0
#> 195 11.76 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 78 23.88 1 43 0 0
#> 56.1 12.21 1 60 0 0
#> 81.1 14.06 1 34 0 0
#> 37 12.52 1 57 1 0
#> 92.1 22.92 1 47 0 1
#> 194 22.40 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 10.1 10.53 1 34 0 0
#> 157 15.10 1 47 0 0
#> 41 18.02 1 40 1 0
#> 158.1 20.14 1 74 1 0
#> 188 16.16 1 46 0 1
#> 113 22.86 1 34 0 0
#> 159.3 10.55 1 50 0 1
#> 68.1 20.62 1 44 0 0
#> 128.1 20.35 1 35 0 1
#> 86 23.81 1 58 0 1
#> 180.1 14.82 1 37 0 0
#> 45 17.42 1 54 0 1
#> 66.1 22.13 1 53 0 0
#> 155 13.08 1 26 0 0
#> 100 16.07 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 101.1 9.97 1 10 0 1
#> 70.1 7.38 1 30 1 0
#> 153.1 21.33 1 55 1 0
#> 11 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 172 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 193 24.00 0 45 0 1
#> 147 24.00 0 76 1 0
#> 160 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 83 24.00 0 6 0 0
#> 62 24.00 0 71 0 0
#> 22 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 147.1 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 20 24.00 0 46 1 0
#> 162 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 67 24.00 0 25 0 0
#> 20.1 24.00 0 46 1 0
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 160.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 172.1 24.00 0 41 0 0
#> 162.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 22.1 24.00 0 52 1 0
#> 193.1 24.00 0 45 0 1
#> 119 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 126 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 22.2 24.00 0 52 1 0
#> 185 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 112 24.00 0 61 0 0
#> 126.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 84 24.00 0 39 0 1
#> 112.1 24.00 0 61 0 0
#> 102.1 24.00 0 49 0 0
#> 118.1 24.00 0 44 1 0
#> 62.2 24.00 0 71 0 0
#> 64.1 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 95 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 151.1 24.00 0 42 0 0
#> 160.2 24.00 0 31 1 0
#> 146 24.00 0 63 1 0
#> 27.1 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#> 1.1 24.00 0 23 1 0
#> 73 24.00 0 NA 0 1
#> 156.1 24.00 0 50 1 0
#> 142.1 24.00 0 53 0 0
#> 84.1 24.00 0 39 0 1
#> 103 24.00 0 56 1 0
#> 20.2 24.00 0 46 1 0
#> 163.1 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 103.1 24.00 0 56 1 0
#> 95.1 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 47 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 64.2 24.00 0 43 0 0
#> 47.1 24.00 0 38 0 1
#> 178 24.00 0 52 1 0
#> 178.1 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 98 24.00 0 34 1 0
#> 17.1 24.00 0 38 0 1
#> 132.1 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 186 24.00 0 45 1 0
#> 182.1 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.369 NA NA NA
#> 2 age, Cure model 0.00485 NA NA NA
#> 3 grade_ii, Cure model -0.113 NA NA NA
#> 4 grade_iii, Cure model 1.26 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00381 NA NA NA
#> 2 grade_ii, Survival model 0.551 NA NA NA
#> 3 grade_iii, Survival model 0.318 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.369412 0.004853 -0.113285 1.256025
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 248.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.3694119 0.0048528 -0.1132853 1.2560246
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00381439 0.55129211 0.31773585
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.134261673 0.864727315 0.302112897 0.539520123 0.610810398 0.474691072
#> [7] 0.619775775 0.446409301 0.211591677 0.232238565 0.974875352 0.619775775
#> [13] 0.864727315 0.804157789 0.830186773 0.282408966 0.252585868 0.530327837
#> [19] 0.539520123 0.232238565 0.991631217 0.101475190 0.511931309 0.051638743
#> [25] 0.388890379 0.417426587 0.924228655 0.949708477 0.778092323 0.856101469
#> [31] 0.200554642 0.575051696 0.575051696 0.089745557 0.388890379 0.262915634
#> [37] 0.637402677 0.077624322 0.760683095 0.167281847 0.465276038 0.838865429
#> [43] 0.725733739 0.484092631 0.008404775 0.983256453 0.646295033 0.864727315
#> [49] 0.915645044 0.427122414 0.064663799 0.655163822 0.008404775 0.778092323
#> [55] 0.388890379 0.484092631 0.360067738 0.189311224 0.769406702 0.455886647
#> [61] 0.350382535 0.812839891 0.838865429 0.958176035 0.321560771 0.379219617
#> [67] 0.690449389 0.898538049 0.708126693 0.539520123 0.699294645 0.743351138
#> [73] 0.360067738 0.941214862 0.539520123 0.511931309 0.340652663 0.262915634
#> [79] 0.672824751 0.743351138 0.026703058 0.812839891 0.708126693 0.795462565
#> [85] 0.101475190 0.145774177 0.145774177 0.898538049 0.663984648 0.436817999
#> [91] 0.321560771 0.592870137 0.122906358 0.864727315 0.282408966 0.302112897
#> [97] 0.039351965 0.672824751 0.502607502 0.167281847 0.734537451 0.601826591
#> [103] 0.924228655 0.958176035 0.211591677 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 169 159 128 5 26 110 125 40 153 36 77 125.1 159.1
#> 22.41 10.55 20.35 16.43 15.77 17.56 15.65 18.00 21.33 21.19 7.27 15.65 10.55
#> 42 49 68 90 192 5.1 99 127 92 130 168 8 108
#> 12.43 12.19 20.62 20.94 16.44 16.43 21.19 3.53 22.92 16.47 23.72 18.43 18.29
#> 101 183 177 107 197 79 79.1 69 8.1 32 6 129 14
#> 9.97 9.24 12.53 11.18 21.60 16.23 16.23 23.23 18.43 20.90 15.64 23.41 12.89
#> 66 184 43 60 111 24 91 39 159.2 52 51 164 167
#> 22.13 17.77 12.10 13.15 17.45 23.89 5.33 15.59 10.55 10.42 18.23 23.60 15.55
#> 24.1 177.1 8.2 111.1 58 136 140 134 170 56 43.1 70 158
#> 23.89 12.53 18.43 17.45 19.34 21.83 12.68 17.81 19.54 12.21 12.10 7.38 20.14
#> 76 96 10 81 5.2 13 123 55 187 5.3 130.1 166 32.1
#> 19.22 14.54 10.53 14.06 16.43 14.34 13.00 19.34 9.92 16.43 16.47 19.98 20.90
#> 180 123.1 78 56.1 81.1 37 92.1 194 194.1 10.1 157 41 158.1
#> 14.82 13.00 23.88 12.21 14.06 12.52 22.92 22.40 22.40 10.53 15.10 18.02 20.14
#> 188 113 159.3 68.1 128.1 86 180.1 45 66.1 155 100 101.1 70.1
#> 16.16 22.86 10.55 20.62 20.35 23.81 14.82 17.42 22.13 13.08 16.07 9.97 7.38
#> 153.1 11 141 172 191 193 147 160 48 142 83 62 22
#> 21.33 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 147.1 17 20 162 118 156 67 20.1 182 2 102 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 160.1 33 33.1 172.1 162.1 163 72 22.1 193.1 119 104 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 126 1 22.2 185 62.1 200 112 126.1 19 84 112.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 62.2 64.1 151 95 27 151.1 160.2 146 27.1 48.1 1.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 84.1 103 20.2 163.1 75 103.1 95.1 116 47 132 64.2 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178 178.1 174 98 17.1 132.1 7 196 186 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[21]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01097571 0.43937243 0.34284137
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.098005489 0.001321749 0.005662998
#> grade_iii, Cure model
#> 0.605195002
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 188 16.16 1 46 0 1
#> 180 14.82 1 37 0 0
#> 59 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 68 20.62 1 44 0 0
#> 56 12.21 1 60 0 0
#> 60 13.15 1 38 1 0
#> 113 22.86 1 34 0 0
#> 153 21.33 1 55 1 0
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 55 19.34 1 69 0 1
#> 129 23.41 1 53 1 0
#> 37 12.52 1 57 1 0
#> 197 21.60 1 69 1 0
#> 169 22.41 1 46 0 0
#> 136 21.83 1 43 0 1
#> 130 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 32 20.90 1 37 1 0
#> 188.1 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 199 19.81 1 NA 0 1
#> 45 17.42 1 54 0 1
#> 8 18.43 1 32 0 0
#> 37.1 12.52 1 57 1 0
#> 40 18.00 1 28 1 0
#> 181 16.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 15 22.68 1 48 0 0
#> 111 17.45 1 47 0 1
#> 123.1 13.00 1 44 1 0
#> 139 21.49 1 63 1 0
#> 169.1 22.41 1 46 0 0
#> 51 18.23 1 83 0 1
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 61 10.12 1 36 0 1
#> 79 16.23 1 54 1 0
#> 180.1 14.82 1 37 0 0
#> 166 19.98 1 48 0 0
#> 188.2 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 113.1 22.86 1 34 0 0
#> 92 22.92 1 47 0 1
#> 78 23.88 1 43 0 0
#> 105 19.75 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 42 12.43 1 49 0 1
#> 157 15.10 1 47 0 0
#> 40.1 18.00 1 28 1 0
#> 45.1 17.42 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 55.1 19.34 1 69 0 1
#> 107 11.18 1 54 1 0
#> 199.1 19.81 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 81 14.06 1 34 0 0
#> 106 16.67 1 49 1 0
#> 117 17.46 1 26 0 1
#> 18.1 15.21 1 49 1 0
#> 56.1 12.21 1 60 0 0
#> 13 14.34 1 54 0 1
#> 159 10.55 1 50 0 1
#> 134.1 17.81 1 47 1 0
#> 166.1 19.98 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 117.1 17.46 1 26 0 1
#> 5.1 16.43 1 51 0 1
#> 189 10.51 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 89 11.44 1 NA 0 0
#> 32.2 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 189.1 10.51 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 145 10.07 1 65 1 0
#> 36.1 21.19 1 48 0 1
#> 107.1 11.18 1 54 1 0
#> 36.2 21.19 1 48 0 1
#> 55.2 19.34 1 69 0 1
#> 39 15.59 1 37 0 1
#> 167 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 197.1 21.60 1 69 1 0
#> 76.1 19.22 1 54 0 1
#> 86 23.81 1 58 0 1
#> 166.2 19.98 1 48 0 0
#> 128 20.35 1 35 0 1
#> 59.1 10.16 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 51.1 18.23 1 83 0 1
#> 32.3 20.90 1 37 1 0
#> 164 23.60 1 76 0 1
#> 128.1 20.35 1 35 0 1
#> 140.1 12.68 1 59 1 0
#> 111.1 17.45 1 47 0 1
#> 45.2 17.42 1 54 0 1
#> 15.1 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 177.1 12.53 1 75 0 0
#> 136.1 21.83 1 43 0 1
#> 129.2 23.41 1 53 1 0
#> 45.3 17.42 1 54 0 1
#> 112 24.00 0 61 0 0
#> 22 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 135 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 62 24.00 0 71 0 0
#> 94 24.00 0 51 0 1
#> 200 24.00 0 64 0 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 162 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 156 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 162.1 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 47 24.00 0 38 0 1
#> 38 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 72 24.00 0 40 0 1
#> 47.1 24.00 0 38 0 1
#> 137 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 163 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 20 24.00 0 46 1 0
#> 148.1 24.00 0 61 1 0
#> 28 24.00 0 67 1 0
#> 152 24.00 0 36 0 1
#> 186 24.00 0 45 1 0
#> 112.1 24.00 0 61 0 0
#> 156.1 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 198 24.00 0 66 0 1
#> 20.1 24.00 0 46 1 0
#> 73 24.00 0 NA 0 1
#> 116.2 24.00 0 58 0 1
#> 65 24.00 0 57 1 0
#> 17 24.00 0 38 0 1
#> 82.1 24.00 0 34 0 0
#> 146 24.00 0 63 1 0
#> 28.1 24.00 0 67 1 0
#> 3 24.00 0 31 1 0
#> 116.3 24.00 0 58 0 1
#> 80 24.00 0 41 0 0
#> 35 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 48 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 152.1 24.00 0 36 0 1
#> 148.2 24.00 0 61 1 0
#> 21 24.00 0 47 0 0
#> 84.1 24.00 0 39 0 1
#> 20.2 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 135.1 24.00 0 58 1 0
#> 33.1 24.00 0 53 0 0
#> 28.2 24.00 0 67 1 0
#> 65.1 24.00 0 57 1 0
#> 98.1 24.00 0 34 1 0
#> 83.1 24.00 0 6 0 0
#> 118.1 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 161 24.00 0 45 0 0
#> 132 24.00 0 55 0 0
#> 148.3 24.00 0 61 1 0
#> 165 24.00 0 47 0 0
#> 162.2 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 35.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 152.2 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.0980 NA NA NA
#> 2 age, Cure model 0.00132 NA NA NA
#> 3 grade_ii, Cure model 0.00566 NA NA NA
#> 4 grade_iii, Cure model 0.605 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0110 NA NA NA
#> 2 grade_ii, Survival model 0.439 NA NA NA
#> 3 grade_iii, Survival model 0.343 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.098005 0.001322 0.005663 0.605195
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 257.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.098005489 0.001321749 0.005662998 0.605195002
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01097571 0.43937243 0.34284137
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7033468454 0.9388291856 0.9755954592 0.5807154017 0.6806322582
#> [6] 0.2052687965 0.8663336684 0.7378474785 0.0386528397 0.1288038105
#> [11] 0.3995593288 0.3369749552 0.2785331214 0.0179996393 0.8307338101
#> [16] 0.1034310000 0.0645028172 0.0875156948 0.5151945446 0.3168968356
#> [21] 0.1633190018 0.5807154017 0.6469955831 0.4624066783 0.3472833651
#> [26] 0.8307338101 0.3787028155 0.5260933779 0.7609871805 0.0509024208
#> [31] 0.4413725034 0.7609871805 0.1200465043 0.0645028172 0.3576832195
#> [36] 0.1376524637 0.0069295252 0.9510667811 0.5696966169 0.6806322582
#> [41] 0.2319811285 0.5807154017 0.8071895711 0.0386528397 0.0326153291
#> [46] 0.0006718871 0.2592775094 0.1633190018 0.8903698199 0.2785331214
#> [51] 0.8543920251 0.6693058546 0.3787028155 0.4624066783 0.0179996393
#> [56] 0.2785331214 0.9024839080 0.5479314314 0.5370239677 0.7262957296
#> [61] 0.5043444895 0.4204965477 0.6469955831 0.8663336684 0.7148009251
#> [66] 0.9266410729 0.3995593288 0.2319811285 0.9755954592 0.4204965477
#> [71] 0.5479314314 0.7493951552 0.1633190018 0.1964073415 0.6134221633
#> [76] 0.9633124053 0.1376524637 0.9024839080 0.1376524637 0.2785331214
#> [81] 0.6245945482 0.6357792023 0.7840243896 0.1034310000 0.3168968356
#> [86] 0.0033382988 0.2319811285 0.2142792806 0.0793521109 0.3576832195
#> [91] 0.1633190018 0.0119571765 0.2142792806 0.7840243896 0.4413725034
#> [96] 0.4624066783 0.0509024208 0.2688844209 0.8071895711 0.0875156948
#> [101] 0.0179996393 0.4624066783 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 96 10 187 188 180 68 56 60 113 153 134 179 55
#> 14.54 10.53 9.92 16.16 14.82 20.62 12.21 13.15 22.86 21.33 17.81 18.63 19.34
#> 129 37 197 169 136 130 76 32 188.1 18 45 8 37.1
#> 23.41 12.52 21.60 22.41 21.83 16.47 19.22 20.90 16.16 15.21 17.42 18.43 12.52
#> 40 181 123 15 111 123.1 139 169.1 51 36 168 61 79
#> 18.00 16.46 13.00 22.68 17.45 13.00 21.49 22.41 18.23 21.19 23.72 10.12 16.23
#> 180.1 166 188.2 177 113.1 92 78 105 32.1 49 58 42 157
#> 14.82 19.98 16.16 12.53 22.86 22.92 23.88 19.75 20.90 12.19 19.34 12.43 15.10
#> 40.1 45.1 129.1 55.1 107 5 192 81 106 117 18.1 56.1 13
#> 18.00 17.42 23.41 19.34 11.18 16.43 16.44 14.06 16.67 17.46 15.21 12.21 14.34
#> 159 134.1 166.1 187.1 117.1 5.1 155 32.2 190 6 145 36.1 107.1
#> 10.55 17.81 19.98 9.92 17.46 16.43 13.08 20.90 20.81 15.64 10.07 21.19 11.18
#> 36.2 55.2 39 167 140 197.1 76.1 86 166.2 128 66 51.1 32.3
#> 21.19 19.34 15.59 15.55 12.68 21.60 19.22 23.81 19.98 20.35 22.13 18.23 20.90
#> 164 128.1 140.1 111.1 45.2 15.1 170 177.1 136.1 129.2 45.3 112 22
#> 23.60 20.35 12.68 17.45 17.42 22.68 19.54 12.53 21.83 23.41 17.42 24.00 24.00
#> 191 135 173 62 94 200 19 116 162 54 156 118 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.1 116.1 98 33 82 47 38 148 72 47.1 137 191.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 95 120 163 22.1 9 185 119 141 126 44 20 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 152 186 112.1 156.1 84 198 20.1 116.2 65 17 82.1 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 3 116.3 80 35 151 48 137.1 102 152.1 148.2 21 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 1 135.1 33.1 28.2 65.1 98.1 83.1 118.1 122 53 161 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.3 165 162.2 12 35.1 160 152.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[22]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001432574 0.494984909 0.449349994
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.424585236 0.006084426 0.699846739
#> grade_iii, Cure model
#> 0.254322788
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 88 18.37 1 47 0 0
#> 88.1 18.37 1 47 0 0
#> 184 17.77 1 38 0 0
#> 140 12.68 1 59 1 0
#> 108 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 15 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 41 18.02 1 40 1 0
#> 25 6.32 1 34 1 0
#> 91.1 5.33 1 61 0 1
#> 140.1 12.68 1 59 1 0
#> 43 12.10 1 61 0 1
#> 166 19.98 1 48 0 0
#> 190 20.81 1 42 1 0
#> 69 23.23 1 25 0 1
#> 123 13.00 1 44 1 0
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 36 21.19 1 48 0 1
#> 41.1 18.02 1 40 1 0
#> 63 22.77 1 31 1 0
#> 93 10.33 1 52 0 1
#> 63.1 22.77 1 31 1 0
#> 150 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 113 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 188 16.16 1 46 0 1
#> 78.1 23.88 1 43 0 0
#> 63.2 22.77 1 31 1 0
#> 192 16.44 1 31 1 0
#> 154 12.63 1 20 1 0
#> 60 13.15 1 38 1 0
#> 5 16.43 1 51 0 1
#> 18 15.21 1 49 1 0
#> 168 23.72 1 70 0 0
#> 157.1 15.10 1 47 0 0
#> 197 21.60 1 69 1 0
#> 70 7.38 1 30 1 0
#> 68 20.62 1 44 0 0
#> 195 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 8 18.43 1 32 0 0
#> 124 9.73 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 90 20.94 1 50 0 1
#> 77 7.27 1 67 0 1
#> 16 8.71 1 71 0 1
#> 56 12.21 1 60 0 0
#> 92 22.92 1 47 0 1
#> 187 9.92 1 39 1 0
#> 6 15.64 1 39 0 0
#> 59 10.16 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 76 19.22 1 54 0 1
#> 154.1 12.63 1 20 1 0
#> 45 17.42 1 54 0 1
#> 4 17.64 1 NA 0 1
#> 24 23.89 1 38 0 0
#> 30 17.43 1 78 0 0
#> 108.1 18.29 1 39 0 1
#> 4.1 17.64 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 190.1 20.81 1 42 1 0
#> 187.1 9.92 1 39 1 0
#> 111.1 17.45 1 47 0 1
#> 129.1 23.41 1 53 1 0
#> 106 16.67 1 49 1 0
#> 105 19.75 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 189 10.51 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 6.1 15.64 1 39 0 0
#> 195.1 11.76 1 NA 1 0
#> 197.1 21.60 1 69 1 0
#> 5.1 16.43 1 51 0 1
#> 76.1 19.22 1 54 0 1
#> 29 15.45 1 68 1 0
#> 149 8.37 1 33 1 0
#> 181 16.46 1 45 0 1
#> 52 10.42 1 52 0 1
#> 168.1 23.72 1 70 0 0
#> 81 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 180 14.82 1 37 0 0
#> 180.1 14.82 1 37 0 0
#> 166.1 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 93.1 10.33 1 52 0 1
#> 145 10.07 1 65 1 0
#> 40.1 18.00 1 28 1 0
#> 128 20.35 1 35 0 1
#> 91.2 5.33 1 61 0 1
#> 23 16.92 1 61 0 0
#> 107.1 11.18 1 54 1 0
#> 184.1 17.77 1 38 0 0
#> 179 18.63 1 42 0 0
#> 158 20.14 1 74 1 0
#> 63.3 22.77 1 31 1 0
#> 90.1 20.94 1 50 0 1
#> 76.2 19.22 1 54 0 1
#> 86.1 23.81 1 58 0 1
#> 101 9.97 1 10 0 1
#> 91.3 5.33 1 61 0 1
#> 59.1 10.16 1 NA 1 0
#> 143 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 53 24.00 0 32 0 1
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 142 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 71 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 119 24.00 0 17 0 0
#> 161 24.00 0 45 0 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 72 24.00 0 40 0 1
#> 12.1 24.00 0 63 0 0
#> 53.1 24.00 0 32 0 1
#> 84 24.00 0 39 0 1
#> 151 24.00 0 42 0 0
#> 182 24.00 0 35 0 0
#> 144 24.00 0 28 0 1
#> 20 24.00 0 46 1 0
#> 126 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 72.1 24.00 0 40 0 1
#> 162 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 163 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 84.1 24.00 0 39 0 1
#> 147 24.00 0 76 1 0
#> 17 24.00 0 38 0 1
#> 71.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 94.1 24.00 0 51 0 1
#> 115 24.00 0 NA 1 0
#> 11 24.00 0 42 0 1
#> 74 24.00 0 43 0 1
#> 71.2 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 20.1 24.00 0 46 1 0
#> 176 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 20.2 24.00 0 46 1 0
#> 115.1 24.00 0 NA 1 0
#> 72.2 24.00 0 40 0 1
#> 19 24.00 0 57 0 1
#> 103 24.00 0 56 1 0
#> 82 24.00 0 34 0 0
#> 71.3 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 121 24.00 0 57 1 0
#> 176.1 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 120 24.00 0 68 0 1
#> 121.1 24.00 0 57 1 0
#> 137.2 24.00 0 45 1 0
#> 9 24.00 0 31 1 0
#> 94.2 24.00 0 51 0 1
#> 116.1 24.00 0 58 0 1
#> 84.2 24.00 0 39 0 1
#> 94.3 24.00 0 51 0 1
#> 200 24.00 0 64 0 0
#> 144.1 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 120.1 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 193.1 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 200.1 24.00 0 64 0 0
#> 191 24.00 0 60 0 1
#> 47 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 112.1 24.00 0 61 0 0
#> 72.3 24.00 0 40 0 1
#> 160.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 46.1 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.425 NA NA NA
#> 2 age, Cure model 0.00608 NA NA NA
#> 3 grade_ii, Cure model 0.700 NA NA NA
#> 4 grade_iii, Cure model 0.254 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00143 NA NA NA
#> 2 grade_ii, Survival model 0.495 NA NA NA
#> 3 grade_iii, Survival model 0.449 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.424585 0.006084 0.699847 0.254323
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.3
#> Residual Deviance: 255.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.424585236 0.006084426 0.699846739 0.254322788
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001432574 0.494984909 0.449349994
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.8452034 0.7641220 0.0550789 0.5189855 0.5189855 0.5888818 0.8016978
#> [8] 0.5370453 0.8735816 0.9746770 0.2974600 0.3325223 0.5547147 0.9681622
#> [15] 0.9746770 0.8016978 0.8523898 0.4353208 0.3756015 0.2064324 0.7942544
#> [22] 0.1755453 0.7259320 0.3437782 0.5547147 0.2509949 0.8875711 0.2509949
#> [29] 0.4156472 0.8595334 0.2363985 0.6057578 0.6871050 0.0550789 0.2509949
#> [36] 0.6633882 0.8163037 0.7793332 0.6714110 0.7182434 0.1398581 0.7259320
#> [43] 0.3097899 0.9485023 0.3955919 0.4642178 0.5098533 0.1032445 0.8307319
#> [50] 0.3547895 0.9616156 0.9351782 0.8379705 0.2217574 0.9150058 0.6949367
#> [57] 0.5719787 0.4737614 0.8163037 0.6306463 0.0213649 0.6223217 0.5370453
#> [64] 0.7564616 0.3756015 0.9150058 0.6057578 0.1755453 0.6471349 0.4545287
#> [71] 0.9485023 0.7793332 0.6949367 0.3097899 0.6714110 0.4737614 0.7104918
#> [78] 0.9418572 0.6552954 0.8805954 0.1398581 0.7717295 0.9284639 0.7412054
#> [85] 0.7412054 0.4353208 0.8875711 0.9013192 0.5719787 0.4056998 0.9746770
#> [92] 0.6388955 0.8595334 0.5888818 0.5007134 0.4255777 0.2509949 0.3547895
#> [99] 0.4737614 0.1032445 0.9081777 0.9746770 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 49 13 78 88 88.1 184 140 108 159 91 15 139 41
#> 12.19 14.34 23.88 18.37 18.37 17.77 12.68 18.29 10.55 5.33 22.68 21.49 18.02
#> 25 91.1 140.1 43 166 190 69 123 129 157 36 41.1 63
#> 6.32 5.33 12.68 12.10 19.98 20.81 23.23 13.00 23.41 15.10 21.19 18.02 22.77
#> 93 63.1 150 107 113 111 188 78.1 63.2 192 154 60 5
#> 10.33 22.77 20.33 11.18 22.86 17.45 16.16 23.88 22.77 16.44 12.63 13.15 16.43
#> 18 168 157.1 197 70 68 55 8 86 177 90 77 16
#> 15.21 23.72 15.10 21.60 7.38 20.62 19.34 18.43 23.81 12.53 20.94 7.27 8.71
#> 56 92 187 6 40 76 154.1 45 24 30 108.1 133 190.1
#> 12.21 22.92 9.92 15.64 18.00 19.22 12.63 17.42 23.89 17.43 18.29 14.65 20.81
#> 187.1 111.1 129.1 106 105 70.1 60.1 6.1 197.1 5.1 76.1 29 149
#> 9.92 17.45 23.41 16.67 19.75 7.38 13.15 15.64 21.60 16.43 19.22 15.45 8.37
#> 181 52 168.1 81 183 180 180.1 166.1 93.1 145 40.1 128 91.2
#> 16.46 10.42 23.72 14.06 9.24 14.82 14.82 19.98 10.33 10.07 18.00 20.35 5.33
#> 23 107.1 184.1 179 158 63.3 90.1 76.2 86.1 101 91.3 143 116
#> 16.92 11.18 17.77 18.63 20.14 22.77 20.94 19.22 23.81 9.97 5.33 24.00 24.00
#> 53 12 21 21.1 142 62 71 80 119 161 94 46 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 72 12.1 53.1 84 151 182 144 20 126 160 28 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 83 163 75 84.1 147 17 71.1 185 112 94.1 11 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.2 109 20.1 176 119.1 20.2 72.2 19 103 82 71.3 137.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 3 161.1 131 3.1 193 120 121.1 137.2 9 94.2 116.1 84.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.3 200 144.1 141 104 120.1 64 193.1 98 200.1 191 47 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 112.1 72.3 160.1 95 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[23]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002148543 0.777703045 0.314870512
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.61597940 0.01092086 -0.10658929
#> grade_iii, Cure model
#> 1.01724614
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 184 17.77 1 38 0 0
#> 30 17.43 1 78 0 0
#> 194 22.40 1 38 0 1
#> 187 9.92 1 39 1 0
#> 183 9.24 1 67 1 0
#> 90 20.94 1 50 0 1
#> 125 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 88 18.37 1 47 0 0
#> 5 16.43 1 51 0 1
#> 177 12.53 1 75 0 0
#> 92 22.92 1 47 0 1
#> 4 17.64 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 111.1 17.45 1 47 0 1
#> 123 13.00 1 44 1 0
#> 125.1 15.65 1 67 1 0
#> 99 21.19 1 38 0 1
#> 113 22.86 1 34 0 0
#> 154 12.63 1 20 1 0
#> 78 23.88 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 111.2 17.45 1 47 0 1
#> 18 15.21 1 49 1 0
#> 39 15.59 1 37 0 1
#> 187.1 9.92 1 39 1 0
#> 39.1 15.59 1 37 0 1
#> 125.2 15.65 1 67 1 0
#> 167 15.55 1 56 1 0
#> 153 21.33 1 55 1 0
#> 149 8.37 1 33 1 0
#> 51.1 18.23 1 83 0 1
#> 159 10.55 1 50 0 1
#> 133 14.65 1 57 0 0
#> 107 11.18 1 54 1 0
#> 171 16.57 1 41 0 1
#> 190 20.81 1 42 1 0
#> 36 21.19 1 48 0 1
#> 30.1 17.43 1 78 0 0
#> 16 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 113.1 22.86 1 34 0 0
#> 68 20.62 1 44 0 0
#> 50 10.02 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 41 18.02 1 40 1 0
#> 117 17.46 1 26 0 1
#> 181 16.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 41.1 18.02 1 40 1 0
#> 18.1 15.21 1 49 1 0
#> 40 18.00 1 28 1 0
#> 188 16.16 1 46 0 1
#> 125.3 15.65 1 67 1 0
#> 85 16.44 1 36 0 0
#> 69 23.23 1 25 0 1
#> 188.1 16.16 1 46 0 1
#> 52 10.42 1 52 0 1
#> 192 16.44 1 31 1 0
#> 159.1 10.55 1 50 0 1
#> 190.1 20.81 1 42 1 0
#> 51.2 18.23 1 83 0 1
#> 125.4 15.65 1 67 1 0
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 25 6.32 1 34 1 0
#> 117.1 17.46 1 26 0 1
#> 30.2 17.43 1 78 0 0
#> 68.1 20.62 1 44 0 0
#> 86.1 23.81 1 58 0 1
#> 187.2 9.92 1 39 1 0
#> 150 20.33 1 48 0 0
#> 111.3 17.45 1 47 0 1
#> 90.2 20.94 1 50 0 1
#> 181.1 16.46 1 45 0 1
#> 88.1 18.37 1 47 0 0
#> 199 19.81 1 NA 0 1
#> 78.1 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 96 14.54 1 33 0 1
#> 91 5.33 1 61 0 1
#> 77 7.27 1 67 0 1
#> 183.1 9.24 1 67 1 0
#> 45 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 79.1 16.23 1 54 1 0
#> 49 12.19 1 48 1 0
#> 30.3 17.43 1 78 0 0
#> 110 17.56 1 65 0 1
#> 157 15.10 1 47 0 0
#> 159.2 10.55 1 50 0 1
#> 184.1 17.77 1 38 0 0
#> 6 15.64 1 39 0 0
#> 159.3 10.55 1 50 0 1
#> 101 9.97 1 10 0 1
#> 192.1 16.44 1 31 1 0
#> 106 16.67 1 49 1 0
#> 189 10.51 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 199.1 19.81 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 171.1 16.57 1 41 0 1
#> 76 19.22 1 54 0 1
#> 50.1 10.02 1 NA 1 0
#> 127.1 3.53 1 62 0 1
#> 175 21.91 1 43 0 0
#> 91.1 5.33 1 61 0 1
#> 127.2 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 135 24.00 0 58 1 0
#> 75 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 75.1 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 7 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 137 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 48 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 185 24.00 0 44 1 0
#> 1.1 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 84 24.00 0 39 0 1
#> 162 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 122 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 19.1 24.00 0 57 0 1
#> 71 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 151 24.00 0 42 0 0
#> 152 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 141 24.00 0 44 1 0
#> 54 24.00 0 53 1 0
#> 54.1 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 119 24.00 0 17 0 0
#> 35 24.00 0 51 0 0
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 182.1 24.00 0 35 0 0
#> 1.2 24.00 0 23 1 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 31.1 24.00 0 36 0 1
#> 138 24.00 0 44 1 0
#> 162.1 24.00 0 51 0 0
#> 22 24.00 0 52 1 0
#> 87 24.00 0 27 0 0
#> 200 24.00 0 64 0 0
#> 115 24.00 0 NA 1 0
#> 126.1 24.00 0 48 0 0
#> 146 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 191 24.00 0 60 0 1
#> 28.1 24.00 0 67 1 0
#> 54.2 24.00 0 53 1 0
#> 147 24.00 0 76 1 0
#> 71.1 24.00 0 51 0 0
#> 119.2 24.00 0 17 0 0
#> 186 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 148 24.00 0 61 1 0
#> 22.1 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 161 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 147.1 24.00 0 76 1 0
#> 148.2 24.00 0 61 1 0
#> 126.2 24.00 0 48 0 0
#> 54.3 24.00 0 53 1 0
#> 173 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 147.2 24.00 0 76 1 0
#> 53.1 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 19.2 24.00 0 57 0 1
#> 47 24.00 0 38 0 1
#> 121.1 24.00 0 57 1 0
#> 126.3 24.00 0 48 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.616 NA NA NA
#> 2 age, Cure model 0.0109 NA NA NA
#> 3 grade_ii, Cure model -0.107 NA NA NA
#> 4 grade_iii, Cure model 1.02 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00215 NA NA NA
#> 2 grade_ii, Survival model 0.778 NA NA NA
#> 3 grade_iii, Survival model 0.315 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.61598 0.01092 -0.10659 1.01725
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.7
#> Residual Deviance: 252.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.61597940 0.01092086 -0.10658929 1.01724614
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002148543 0.777703045 0.314870512
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.45402379 0.51007235 0.58746631 0.19964926 0.92091240 0.93833967
#> [7] 0.30218993 0.72873748 0.55424088 0.43386271 0.69163936 0.86639962
#> [13] 0.14596418 0.80874940 0.55424088 0.84115613 0.72873748 0.26445597
#> [19] 0.16475260 0.85392100 0.03466621 0.30218993 0.55424088 0.78924002
#> [25] 0.76909140 0.92091240 0.76909140 0.72873748 0.78256031 0.25013948
#> [31] 0.95549555 0.45402379 0.88497398 0.81526212 0.87884500 0.63685870
#> [37] 0.33760828 0.26445597 0.58746631 0.94977909 0.41322417 0.16475260
#> [43] 0.35950045 0.85392100 0.48272313 0.53682512 0.65290277 0.82824984
#> [49] 0.48272313 0.78924002 0.50104471 0.71410146 0.72873748 0.66874861
#> [55] 0.12584627 0.71410146 0.90889191 0.66874861 0.88497398 0.33760828
#> [61] 0.45402379 0.72873748 0.08627305 0.26445597 0.84753967 0.83470442
#> [67] 0.96681838 0.53682512 0.58746631 0.35950045 0.08627305 0.92091240
#> [73] 0.38126169 0.55424088 0.30218993 0.65290277 0.43386271 0.03466621
#> [79] 0.39226756 0.82176806 0.97242611 0.96116667 0.93833967 0.62035296
#> [85] 0.69931012 0.69931012 0.87265365 0.58746631 0.52791466 0.80223235
#> [91] 0.88497398 0.51007235 0.76226918 0.88497398 0.91491005 0.66874861
#> [97] 0.62868264 0.98353743 0.40281436 0.63685870 0.42361113 0.98353743
#> [103] 0.21715628 0.97242611 0.98353743 0.23452857 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 51 184 30 194 187 183 90 125 111 88 5 177 92
#> 18.23 17.77 17.43 22.40 9.92 9.24 20.94 15.65 17.45 18.37 16.43 12.53 22.92
#> 180 111.1 123 125.1 99 113 154 78 90.1 111.2 18 39 187.1
#> 14.82 17.45 13.00 15.65 21.19 22.86 12.63 23.88 20.94 17.45 15.21 15.59 9.92
#> 39.1 125.2 167 153 149 51.1 159 133 107 171 190 36 30.1
#> 15.59 15.65 15.55 21.33 8.37 18.23 10.55 14.65 11.18 16.57 20.81 21.19 17.43
#> 16 58 113.1 68 154.1 41 117 181 13 41.1 18.1 40 188
#> 8.71 19.34 22.86 20.62 12.63 18.02 17.46 16.46 14.34 18.02 15.21 18.00 16.16
#> 125.3 85 69 188.1 52 192 159.1 190.1 51.2 125.4 86 36.1 14
#> 15.65 16.44 23.23 16.16 10.42 16.44 10.55 20.81 18.23 15.65 23.81 21.19 12.89
#> 155 25 117.1 30.2 68.1 86.1 187.2 150 111.3 90.2 181.1 88.1 78.1
#> 13.08 6.32 17.46 17.43 20.62 23.81 9.92 20.33 17.45 20.94 16.46 18.37 23.88
#> 158 96 91 77 183.1 45 79 79.1 49 30.3 110 157 159.2
#> 20.14 14.54 5.33 7.27 9.24 17.42 16.23 16.23 12.19 17.43 17.56 15.10 10.55
#> 184.1 6 159.3 101 192.1 106 127 170 171.1 76 127.1 175 91.1
#> 17.77 15.64 10.55 9.97 16.44 16.67 3.53 19.54 16.57 19.22 3.53 21.91 5.33
#> 127.2 197 135 75 19 75.1 46 53 163 31 7 126 137
#> 3.53 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 28 48 121 1 185 1.1 95 120 9 64 84 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 122 65 19.1 71 118 83 151 152 94 182 141 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.1 109 119 35 193 3 176 182.1 1.2 104 143 9.1 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 138 162.1 22 87 200 126.1 146 119.1 191 28.1 54.2 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 119.2 186 11 148 22.1 62 44 161 38 148.1 147.1 148.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.2 54.3 173 20 147.2 53.1 196 19.2 47 121.1 126.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[24]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004205119 0.369144490 0.216980924
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.175682031 -0.003023652 0.152761621
#> grade_iii, Cure model
#> 0.262844130
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 96 14.54 1 33 0 1
#> 29 15.45 1 68 1 0
#> 16 8.71 1 71 0 1
#> 99 21.19 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 37 12.52 1 57 1 0
#> 125 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 59 10.16 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 130 16.47 1 53 0 1
#> 190 20.81 1 42 1 0
#> 179 18.63 1 42 0 0
#> 56 12.21 1 60 0 0
#> 57 14.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 56.1 12.21 1 60 0 0
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 25 6.32 1 34 1 0
#> 111 17.45 1 47 0 1
#> 69 23.23 1 25 0 1
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 111.1 17.45 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 157 15.10 1 47 0 0
#> 10 10.53 1 34 0 0
#> 129 23.41 1 53 1 0
#> 86 23.81 1 58 0 1
#> 14 12.89 1 21 0 0
#> 24 23.89 1 38 0 0
#> 66 22.13 1 53 0 0
#> 164 23.60 1 76 0 1
#> 189 10.51 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 188 16.16 1 46 0 1
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 154 12.63 1 20 1 0
#> 150 20.33 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 59.1 10.16 1 NA 1 0
#> 36.1 21.19 1 48 0 1
#> 101.1 9.97 1 10 0 1
#> 63 22.77 1 31 1 0
#> 140 12.68 1 59 1 0
#> 158 20.14 1 74 1 0
#> 139 21.49 1 63 1 0
#> 25.1 6.32 1 34 1 0
#> 41 18.02 1 40 1 0
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 61.1 10.12 1 36 0 1
#> 93.1 10.33 1 52 0 1
#> 184 17.77 1 38 0 0
#> 96.1 14.54 1 33 0 1
#> 55 19.34 1 69 0 1
#> 129.1 23.41 1 53 1 0
#> 184.1 17.77 1 38 0 0
#> 60 13.15 1 38 1 0
#> 23 16.92 1 61 0 0
#> 189.1 10.51 1 NA 1 0
#> 61.2 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 29.1 15.45 1 68 1 0
#> 154.1 12.63 1 20 1 0
#> 52 10.42 1 52 0 1
#> 197 21.60 1 69 1 0
#> 136.1 21.83 1 43 0 1
#> 179.1 18.63 1 42 0 0
#> 23.1 16.92 1 61 0 0
#> 177.1 12.53 1 75 0 0
#> 52.1 10.42 1 52 0 1
#> 111.2 17.45 1 47 0 1
#> 129.2 23.41 1 53 1 0
#> 167 15.55 1 56 1 0
#> 181 16.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 93.2 10.33 1 52 0 1
#> 45 17.42 1 54 0 1
#> 154.2 12.63 1 20 1 0
#> 117 17.46 1 26 0 1
#> 125.2 15.65 1 67 1 0
#> 99.1 21.19 1 38 0 1
#> 189.2 10.51 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 24.1 23.89 1 38 0 0
#> 169.1 22.41 1 46 0 0
#> 93.3 10.33 1 52 0 1
#> 184.2 17.77 1 38 0 0
#> 57.1 14.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 92.1 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 199.1 19.81 1 NA 0 1
#> 70 7.38 1 30 1 0
#> 92.2 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 49.1 12.19 1 48 1 0
#> 26 15.77 1 49 0 1
#> 136.2 21.83 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 140.1 12.68 1 59 1 0
#> 10.1 10.53 1 34 0 0
#> 71 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 87 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 131 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 84.1 24.00 0 39 0 1
#> 119 24.00 0 17 0 0
#> 198 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 193 24.00 0 45 0 1
#> 178 24.00 0 52 1 0
#> 47.1 24.00 0 38 0 1
#> 3.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 94.1 24.00 0 51 0 1
#> 174 24.00 0 49 1 0
#> 22 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 116.1 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 143 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 193.1 24.00 0 45 0 1
#> 178.1 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 131.1 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 147 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 176 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 34 24.00 0 36 0 0
#> 22.1 24.00 0 52 1 0
#> 146 24.00 0 63 1 0
#> 28 24.00 0 67 1 0
#> 104 24.00 0 50 1 0
#> 80 24.00 0 41 0 0
#> 182.1 24.00 0 35 0 0
#> 94.2 24.00 0 51 0 1
#> 19.1 24.00 0 57 0 1
#> 47.2 24.00 0 38 0 1
#> 115 24.00 0 NA 1 0
#> 27 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 73 24.00 0 NA 0 1
#> 116.2 24.00 0 58 0 1
#> 71.1 24.00 0 51 0 0
#> 146.1 24.00 0 63 1 0
#> 19.2 24.00 0 57 0 1
#> 2 24.00 0 9 0 0
#> 53.2 24.00 0 32 0 1
#> 35.1 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 3.2 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 116.3 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 151.1 24.00 0 42 0 0
#> 176.1 24.00 0 43 0 1
#> 95.1 24.00 0 68 0 1
#> 35.2 24.00 0 51 0 0
#> 75.1 24.00 0 21 1 0
#> 198.1 24.00 0 66 0 1
#> 46 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 75.2 24.00 0 21 1 0
#> 126 24.00 0 48 0 0
#> 94.3 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 116.4 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 178.2 24.00 0 52 1 0
#> 74.1 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 115.1 24.00 0 NA 1 0
#> 182.2 24.00 0 35 0 0
#> 174.1 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.176 NA NA NA
#> 2 age, Cure model -0.00302 NA NA NA
#> 3 grade_ii, Cure model 0.153 NA NA NA
#> 4 grade_iii, Cure model 0.263 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00421 NA NA NA
#> 2 grade_ii, Survival model 0.369 NA NA NA
#> 3 grade_iii, Survival model 0.217 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.175682 -0.003024 0.152762 0.262844
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 257.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.175682031 -0.003023652 0.152761621 0.262844130
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004205119 0.369144490 0.216980924
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.631741006 0.592332721 0.951841936 0.232270242 0.758302377 0.553152407
#> [7] 0.922844600 0.346586708 0.503327101 0.269126527 0.327171335 0.768039984
#> [13] 0.651381956 0.183953708 0.768039984 0.173853644 0.990371682 0.971216583
#> [19] 0.424916933 0.077986525 0.893925061 0.317410565 0.232270242 0.424916933
#> [25] 0.553152407 0.611917203 0.816620110 0.050967648 0.026536033 0.680857491
#> [31] 0.008209022 0.163849850 0.038548040 0.453795695 0.855491381 0.523233444
#> [37] 0.738918030 0.806875065 0.533179403 0.710235253 0.278781504 0.942148931
#> [43] 0.232270242 0.922844600 0.125050873 0.690720746 0.288498015 0.222392517
#> [49] 0.971216583 0.366402020 0.356469665 0.134765260 0.893925061 0.855491381
#> [55] 0.386074176 0.631741006 0.298195068 0.050967648 0.386074176 0.671006300
#> [61] 0.473593835 0.893925061 0.088138849 0.592332721 0.710235253 0.836055355
#> [67] 0.212466445 0.183953708 0.327171335 0.473593835 0.738918030 0.836055355
#> [73] 0.424916933 0.050967648 0.582429558 0.513282985 0.621817720 0.855491381
#> [79] 0.463693700 0.710235253 0.415050837 0.553152407 0.232270242 0.153966755
#> [85] 0.008209022 0.134765260 0.855491381 0.386074176 0.651381956 0.376274834
#> [91] 0.088138849 0.493372380 0.961542681 0.088138849 0.115129112 0.787501105
#> [97] 0.298195068 0.787501105 0.543166912 0.183953708 0.690720746 0.816620110
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 96 29 16 99 37 125 101 8 130 190 179 56 57
#> 14.54 15.45 8.71 21.19 12.52 15.65 9.97 18.43 16.47 20.81 18.63 12.21 14.46
#> 136 56.1 175 127 25 111 69 61 76 36 111.1 125.1 157
#> 21.83 12.21 21.91 3.53 6.32 17.45 23.23 10.12 19.22 21.19 17.45 15.65 15.10
#> 10 129 86 14 24 66 164 30 93 188 177 159 100
#> 10.53 23.41 23.81 12.89 23.89 22.13 23.60 17.43 10.33 16.16 12.53 10.55 16.07
#> 154 150 183 36.1 101.1 63 140 158 139 25.1 41 88 169
#> 12.63 20.33 9.24 21.19 9.97 22.77 12.68 20.14 21.49 6.32 18.02 18.37 22.41
#> 61.1 93.1 184 96.1 55 129.1 184.1 60 23 61.2 92 29.1 154.1
#> 10.12 10.33 17.77 14.54 19.34 23.41 17.77 13.15 16.92 10.12 22.92 15.45 12.63
#> 52 197 136.1 179.1 23.1 177.1 52.1 111.2 129.2 167 181 180 93.2
#> 10.42 21.60 21.83 18.63 16.92 12.53 10.42 17.45 23.41 15.55 16.46 14.82 10.33
#> 45 154.2 117 125.2 99.1 194 24.1 169.1 93.3 184.2 57.1 40 92.1
#> 17.42 12.63 17.46 15.65 21.19 22.40 23.89 22.41 10.33 17.77 14.46 18.00 22.92
#> 106 70 92.2 113 49 58 49.1 26 136.2 140.1 10.1 71 94
#> 16.67 7.38 22.92 22.86 12.19 19.34 12.19 15.77 21.83 12.68 10.53 24.00 24.00
#> 87 84 131 186 151 35 116 12 102 84.1 119 198 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 109 65 193 178 47.1 3.1 95 94.1 174 22 72 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 53.1 143 74 193.1 178.1 120 131.1 19 147 182 176 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 34 22.1 146 28 104 80 182.1 94.2 19.1 47.2 27 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.2 71.1 146.1 19.2 2 53.2 35.1 163 3.2 122 116.3 75 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 95.1 35.2 75.1 198.1 46 142 75.2 126 94.3 148 116.4 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.2 74.1 54 182.2 174.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[25]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01385129 0.92761019 0.62725361
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.65560236 0.01833884 -0.13773896
#> grade_iii, Cure model
#> 0.05837717
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 51 18.23 1 83 0 1
#> 150 20.33 1 48 0 0
#> 41 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 93 10.33 1 52 0 1
#> 180 14.82 1 37 0 0
#> 5 16.43 1 51 0 1
#> 41.1 18.02 1 40 1 0
#> 169 22.41 1 46 0 0
#> 16 8.71 1 71 0 1
#> 93.1 10.33 1 52 0 1
#> 183 9.24 1 67 1 0
#> 154 12.63 1 20 1 0
#> 195 11.76 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 32 20.90 1 37 1 0
#> 89 11.44 1 NA 0 0
#> 42 12.43 1 49 0 1
#> 76 19.22 1 54 0 1
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 91 5.33 1 61 0 1
#> 154.1 12.63 1 20 1 0
#> 136 21.83 1 43 0 1
#> 106 16.67 1 49 1 0
#> 36 21.19 1 48 0 1
#> 78 23.88 1 43 0 0
#> 113 22.86 1 34 0 0
#> 113.1 22.86 1 34 0 0
#> 18 15.21 1 49 1 0
#> 140 12.68 1 59 1 0
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 190 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 32.1 20.90 1 37 1 0
#> 187 9.92 1 39 1 0
#> 164.1 23.60 1 76 0 1
#> 155 13.08 1 26 0 0
#> 45.1 17.42 1 54 0 1
#> 41.2 18.02 1 40 1 0
#> 88 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 117.1 17.46 1 26 0 1
#> 56 12.21 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 41.3 18.02 1 40 1 0
#> 61 10.12 1 36 0 1
#> 168 23.72 1 70 0 0
#> 189 10.51 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 169.1 22.41 1 46 0 0
#> 89.1 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 136.1 21.83 1 43 0 1
#> 76.1 19.22 1 54 0 1
#> 169.2 22.41 1 46 0 0
#> 184 17.77 1 38 0 0
#> 56.1 12.21 1 60 0 0
#> 139 21.49 1 63 1 0
#> 130 16.47 1 53 0 1
#> 164.2 23.60 1 76 0 1
#> 139.1 21.49 1 63 1 0
#> 89.2 11.44 1 NA 0 0
#> 56.2 12.21 1 60 0 0
#> 125 15.65 1 67 1 0
#> 169.3 22.41 1 46 0 0
#> 190.1 20.81 1 42 1 0
#> 194 22.40 1 38 0 1
#> 96 14.54 1 33 0 1
#> 50.1 10.02 1 NA 1 0
#> 88.1 18.37 1 47 0 0
#> 130.1 16.47 1 53 0 1
#> 113.2 22.86 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 164.3 23.60 1 76 0 1
#> 149 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 179 18.63 1 42 0 0
#> 78.1 23.88 1 43 0 0
#> 97 19.14 1 65 0 1
#> 55 19.34 1 69 0 1
#> 128 20.35 1 35 0 1
#> 136.2 21.83 1 43 0 1
#> 184.1 17.77 1 38 0 0
#> 66.1 22.13 1 53 0 0
#> 41.4 18.02 1 40 1 0
#> 154.2 12.63 1 20 1 0
#> 157 15.10 1 47 0 0
#> 106.1 16.67 1 49 1 0
#> 124 9.73 1 NA 1 0
#> 66.2 22.13 1 53 0 0
#> 107 11.18 1 54 1 0
#> 41.5 18.02 1 40 1 0
#> 51.1 18.23 1 83 0 1
#> 50.2 10.02 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 184.2 17.77 1 38 0 0
#> 177 12.53 1 75 0 0
#> 188 16.16 1 46 0 1
#> 158 20.14 1 74 1 0
#> 91.1 5.33 1 61 0 1
#> 130.2 16.47 1 53 0 1
#> 42.1 12.43 1 49 0 1
#> 134 17.81 1 47 1 0
#> 155.1 13.08 1 26 0 0
#> 61.1 10.12 1 36 0 1
#> 88.2 18.37 1 47 0 0
#> 190.2 20.81 1 42 1 0
#> 167 15.55 1 56 1 0
#> 122 24.00 0 66 0 0
#> 95 24.00 0 68 0 1
#> 162 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 48 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 1 24.00 0 23 1 0
#> 95.1 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 94 24.00 0 51 0 1
#> 47.1 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 9 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 17 24.00 0 38 0 1
#> 191 24.00 0 60 0 1
#> 152 24.00 0 36 0 1
#> 147.1 24.00 0 76 1 0
#> 35 24.00 0 51 0 0
#> 95.2 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 74 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 67 24.00 0 25 0 0
#> 144 24.00 0 28 0 1
#> 19.1 24.00 0 57 0 1
#> 75.1 24.00 0 21 1 0
#> 146 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 191.1 24.00 0 60 0 1
#> 109 24.00 0 48 0 0
#> 83 24.00 0 6 0 0
#> 64.1 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 173 24.00 0 19 0 1
#> 35.1 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#> 94.1 24.00 0 51 0 1
#> 47.2 24.00 0 38 0 1
#> 82.1 24.00 0 34 0 0
#> 178 24.00 0 52 1 0
#> 143 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 75.2 24.00 0 21 1 0
#> 3 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 3.1 24.00 0 31 1 0
#> 2 24.00 0 9 0 0
#> 135 24.00 0 58 1 0
#> 196 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 176.1 24.00 0 43 0 1
#> 174 24.00 0 49 1 0
#> 176.2 24.00 0 43 0 1
#> 47.3 24.00 0 38 0 1
#> 22.1 24.00 0 52 1 0
#> 135.1 24.00 0 58 1 0
#> 73.1 24.00 0 NA 0 1
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 176.3 24.00 0 43 0 1
#> 191.2 24.00 0 60 0 1
#> 80 24.00 0 41 0 0
#> 185 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 35.2 24.00 0 51 0 0
#> 80.1 24.00 0 41 0 0
#> 95.3 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 47.4 24.00 0 38 0 1
#> 82.2 24.00 0 34 0 0
#> 178.1 24.00 0 52 1 0
#> 185.1 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#> 173.1 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 28 24.00 0 67 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.656 NA NA NA
#> 2 age, Cure model 0.0183 NA NA NA
#> 3 grade_ii, Cure model -0.138 NA NA NA
#> 4 grade_iii, Cure model 0.0584 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0139 NA NA NA
#> 2 grade_ii, Survival model 0.928 NA NA NA
#> 3 grade_iii, Survival model 0.627 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65560 0.01834 -0.13774 0.05838
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 253.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.65560236 0.01833884 -0.13773896 0.05837717
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01385129 0.92761019 0.62725361
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3954318052 0.2714943538 0.4174401365 0.5589732983 0.8842023530
#> [6] 0.7163764684 0.6318463237 0.4174401365 0.0527496889 0.9475825075
#> [11] 0.8842023530 0.9370280042 0.7697507140 0.0120166570 0.2129286336
#> [16] 0.8107239954 0.3115247088 0.2914280309 0.5484163685 0.1805877298
#> [21] 0.6423936402 0.9791364985 0.7697507140 0.1279185308 0.5799772244
#> [26] 0.1805877298 0.0009972661 0.0319109293 0.0319109293 0.6952250841
#> [31] 0.7590288083 0.6634220176 0.8735762511 0.2333144974 0.9686923527
#> [36] 0.2129286336 0.9264735528 0.0120166570 0.7377015484 0.5589732983
#> [41] 0.4174401365 0.3526282751 0.5277657593 0.5277657593 0.8314324334
#> [46] 0.4174401365 0.9053717982 0.0061189555 0.0964642847 0.0527496889
#> [51] 0.2019245330 0.1279185308 0.3115247088 0.0527496889 0.4863311784
#> [56] 0.8314324334 0.1591663522 0.6007684620 0.0120166570 0.1591663522
#> [61] 0.8314324334 0.6740319593 0.0527496889 0.2333144974 0.0865187517
#> [66] 0.7270535097 0.3526282751 0.6007684620 0.0319109293 0.0120166570
#> [71] 0.9581723575 0.3845208903 0.3421291778 0.0009972661 0.3317703093
#> [76] 0.2914280309 0.2617179443 0.1279185308 0.4863311784 0.0964642847
#> [81] 0.4174401365 0.7697507140 0.7057628625 0.5799772244 0.0964642847
#> [86] 0.8629616185 0.4174401365 0.3954318052 0.5172097500 0.4863311784
#> [91] 0.8003162334 0.6529069926 0.2814447996 0.9791364985 0.6007684620
#> [96] 0.8107239954 0.4760847532 0.7377015484 0.9053717982 0.3526282751
#> [101] 0.2333144974 0.6846419757 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 51 150 41 45 93 180 5 41.1 169 16 93.1 183 154
#> 18.23 20.33 18.02 17.42 10.33 14.82 16.43 18.02 22.41 8.71 10.33 9.24 12.63
#> 164 32 42 76 58 30 99 79 91 154.1 136 106 36
#> 23.60 20.90 12.43 19.22 19.34 17.43 21.19 16.23 5.33 12.63 21.83 16.67 21.19
#> 78 113 113.1 18 140 100 52 190 70 32.1 187 164.1 155
#> 23.88 22.86 22.86 15.21 12.68 16.07 10.42 20.81 7.38 20.90 9.92 23.60 13.08
#> 45.1 41.2 88 117 117.1 56 41.3 61 168 66 169.1 90 136.1
#> 17.42 18.02 18.37 17.46 17.46 12.21 18.02 10.12 23.72 22.13 22.41 20.94 21.83
#> 76.1 169.2 184 56.1 139 130 164.2 139.1 56.2 125 169.3 190.1 194
#> 19.22 22.41 17.77 12.21 21.49 16.47 23.60 21.49 12.21 15.65 22.41 20.81 22.40
#> 96 88.1 130.1 113.2 164.3 149 108 179 78.1 97 55 128 136.2
#> 14.54 18.37 16.47 22.86 23.60 8.37 18.29 18.63 23.88 19.14 19.34 20.35 21.83
#> 184.1 66.1 41.4 154.2 157 106.1 66.2 107 41.5 51.1 110 184.2 177
#> 17.77 22.13 18.02 12.63 15.10 16.67 22.13 11.18 18.02 18.23 17.56 17.77 12.53
#> 188 158 91.1 130.2 42.1 134 155.1 61.1 88.2 190.2 167 122 95
#> 16.16 20.14 5.33 16.47 12.43 17.81 13.08 10.12 18.37 20.81 15.55 24.00 24.00
#> 162 132 98 48 47 1 95.1 75 142 156 94 47.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 64 9 148 17 191 152 147.1 35 95.2 19 74 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 67 144 19.1 75.1 146 22 191.1 109 83 64.1 132.1 173
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 17.1 94.1 47.2 82.1 178 143 126 75.2 3 176 3.1 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 196 121 176.1 174 176.2 47.3 22.1 135.1 120 71 33 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.3 191.2 80 185 131 9.1 35.2 80.1 95.3 7 47.4 82.2 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 182.1 173.1 141 28
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[26]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02264351 0.87466727 0.41900891
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.86590320 0.01993314 -0.09596565
#> grade_iii, Cure model
#> 0.85805447
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 154 12.63 1 20 1 0
#> 58 19.34 1 39 0 0
#> 167 15.55 1 56 1 0
#> 157 15.10 1 47 0 0
#> 45 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 134 17.81 1 47 1 0
#> 68 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 29 15.45 1 68 1 0
#> 51 18.23 1 83 0 1
#> 18 15.21 1 49 1 0
#> 158 20.14 1 74 1 0
#> 108 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 154.1 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 127 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 13 14.34 1 54 0 1
#> 36 21.19 1 48 0 1
#> 171 16.57 1 41 0 1
#> 183 9.24 1 67 1 0
#> 139 21.49 1 63 1 0
#> 36.1 21.19 1 48 0 1
#> 177 12.53 1 75 0 0
#> 158.1 20.14 1 74 1 0
#> 153 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 23 16.92 1 61 0 0
#> 99 21.19 1 38 0 1
#> 14 12.89 1 21 0 0
#> 167.1 15.55 1 56 1 0
#> 188 16.16 1 46 0 1
#> 154.2 12.63 1 20 1 0
#> 39 15.59 1 37 0 1
#> 181 16.46 1 45 0 1
#> 181.1 16.46 1 45 0 1
#> 32 20.90 1 37 1 0
#> 25 6.32 1 34 1 0
#> 169 22.41 1 46 0 0
#> 169.1 22.41 1 46 0 0
#> 101 9.97 1 10 0 1
#> 68.1 20.62 1 44 0 0
#> 101.1 9.97 1 10 0 1
#> 86 23.81 1 58 0 1
#> 68.2 20.62 1 44 0 0
#> 58.1 19.34 1 39 0 0
#> 61 10.12 1 36 0 1
#> 140 12.68 1 59 1 0
#> 139.1 21.49 1 63 1 0
#> 101.2 9.97 1 10 0 1
#> 70 7.38 1 30 1 0
#> 36.2 21.19 1 48 0 1
#> 149 8.37 1 33 1 0
#> 158.2 20.14 1 74 1 0
#> 36.3 21.19 1 48 0 1
#> 37 12.52 1 57 1 0
#> 89 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 170 19.54 1 43 0 1
#> 169.2 22.41 1 46 0 0
#> 170.1 19.54 1 43 0 1
#> 60 13.15 1 38 1 0
#> 111 17.45 1 47 0 1
#> 171.1 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 155 13.08 1 26 0 0
#> 153.1 21.33 1 55 1 0
#> 86.1 23.81 1 58 0 1
#> 76 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 154.3 12.63 1 20 1 0
#> 25.1 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 181.2 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 150.1 20.33 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 6 15.64 1 39 0 0
#> 188.1 16.16 1 46 0 1
#> 169.3 22.41 1 46 0 0
#> 96 14.54 1 33 0 1
#> 149.1 8.37 1 33 1 0
#> 24 23.89 1 38 0 0
#> 43 12.10 1 61 0 1
#> 194 22.40 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 26 15.77 1 49 0 1
#> 159.1 10.55 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 16 8.71 1 71 0 1
#> 107 11.18 1 54 1 0
#> 169.4 22.41 1 46 0 0
#> 45.1 17.42 1 54 0 1
#> 175 21.91 1 43 0 0
#> 106 16.67 1 49 1 0
#> 32.1 20.90 1 37 1 0
#> 113.1 22.86 1 34 0 0
#> 51.1 18.23 1 83 0 1
#> 166 19.98 1 48 0 0
#> 49 12.19 1 48 1 0
#> 129 23.41 1 53 1 0
#> 41 18.02 1 40 1 0
#> 29.1 15.45 1 68 1 0
#> 85 16.44 1 36 0 0
#> 92 22.92 1 47 0 1
#> 166.1 19.98 1 48 0 0
#> 139.2 21.49 1 63 1 0
#> 3 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 21 24.00 0 47 0 0
#> 121 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 119 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 104 24.00 0 50 1 0
#> 141.1 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 20 24.00 0 46 1 0
#> 75 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 31.1 24.00 0 36 0 1
#> 35 24.00 0 51 0 0
#> 196.1 24.00 0 19 0 0
#> 135 24.00 0 58 1 0
#> 82 24.00 0 34 0 0
#> 119.1 24.00 0 17 0 0
#> 174 24.00 0 49 1 0
#> 126.1 24.00 0 48 0 0
#> 185 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 35.1 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 196.2 24.00 0 19 0 0
#> 193 24.00 0 45 0 1
#> 174.1 24.00 0 49 1 0
#> 87 24.00 0 27 0 0
#> 11.1 24.00 0 42 0 1
#> 193.1 24.00 0 45 0 1
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 151 24.00 0 42 0 0
#> 47.1 24.00 0 38 0 1
#> 132 24.00 0 55 0 0
#> 27 24.00 0 63 1 0
#> 137.1 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 186 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 67 24.00 0 25 0 0
#> 44 24.00 0 56 0 0
#> 54 24.00 0 53 1 0
#> 144.1 24.00 0 28 0 1
#> 46.1 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 186.1 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 174.2 24.00 0 49 1 0
#> 28 24.00 0 67 1 0
#> 151.1 24.00 0 42 0 0
#> 31.2 24.00 0 36 0 1
#> 200 24.00 0 64 0 0
#> 48 24.00 0 31 1 0
#> 84.1 24.00 0 39 0 1
#> 17 24.00 0 38 0 1
#> 200.1 24.00 0 64 0 0
#> 44.1 24.00 0 56 0 0
#> 135.1 24.00 0 58 1 0
#> 65.1 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 185.1 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 75.1 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 118.1 24.00 0 44 1 0
#> 132.1 24.00 0 55 0 0
#> 144.2 24.00 0 28 0 1
#> 137.2 24.00 0 45 1 0
#> 174.3 24.00 0 49 1 0
#> 44.2 24.00 0 56 0 0
#> 22 24.00 0 52 1 0
#> 3.1 24.00 0 31 1 0
#> 3.2 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 20.1 24.00 0 46 1 0
#> 75.2 24.00 0 21 1 0
#> 87.1 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.866 NA NA NA
#> 2 age, Cure model 0.0199 NA NA NA
#> 3 grade_ii, Cure model -0.0960 NA NA NA
#> 4 grade_iii, Cure model 0.858 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0226 NA NA NA
#> 2 grade_ii, Survival model 0.875 NA NA NA
#> 3 grade_iii, Survival model 0.419 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86590 0.01993 -0.09597 0.85805
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 268.8
#> Residual Deviance: 258.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.86590320 0.01993314 -0.09596565 0.85805447
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02264351 0.87466727 0.41900891
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 6.433341e-01 1.632262e-01 4.571119e-01 5.203870e-01 2.587123e-01
#> [6] 1.024232e-01 3.521916e-01 2.306583e-01 8.593906e-02 5.335712e-01
#> [11] 4.819461e-01 2.038195e-01 5.074180e-01 1.146239e-01 1.871724e-01
#> [16] 7.057517e-02 6.433341e-01 8.170441e-04 9.850898e-01 2.567923e-02
#> [21] 5.604067e-01 4.862796e-02 2.989951e-01 8.817142e-01 2.927974e-02
#> [26] 4.862796e-02 6.957050e-01 1.146239e-01 4.035812e-02 3.752192e-03
#> [31] 2.783588e-01 4.862796e-02 6.014743e-01 4.571119e-01 3.856268e-01
#> [36] 6.433341e-01 4.447432e-01 3.199188e-01 3.199188e-01 7.583427e-02
#> [41] 9.557711e-01 6.521111e-03 6.521111e-03 8.384696e-01 8.593906e-02
#> [46] 8.384696e-01 1.630014e-04 8.593906e-02 1.632262e-01 8.236343e-01
#> [51] 6.291991e-01 2.927974e-02 8.384696e-01 9.409469e-01 4.862796e-02
#> [56] 9.114326e-01 1.146239e-01 4.862796e-02 7.094012e-01 7.944017e-01
#> [61] 1.483582e-01 6.521111e-03 1.483582e-01 5.740515e-01 2.397980e-01
#> [66] 2.989951e-01 4.085571e-01 5.876917e-01 4.035812e-02 1.630014e-04
#> [71] 1.789338e-01 2.491064e-01 6.433341e-01 9.557711e-01 7.231881e-01
#> [76] 3.199188e-01 3.743030e-01 1.024232e-01 7.231881e-01 6.014743e-01
#> [81] 4.324910e-01 3.856268e-01 6.521111e-03 5.469429e-01 9.114326e-01
#> [86] 1.532563e-05 7.655223e-01 1.650877e-02 1.650877e-02 4.204391e-01
#> [91] 7.944017e-01 1.871724e-01 8.964878e-01 7.799227e-01 6.521111e-03
#> [96] 2.587123e-01 2.228195e-02 2.886383e-01 7.583427e-02 3.752192e-03
#> [101] 2.038195e-01 1.340992e-01 7.512874e-01 1.631748e-03 2.215808e-01
#> [106] 4.819461e-01 3.521916e-01 2.588113e-03 1.340992e-01 2.927974e-02
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [196] 0.000000e+00
#>
#> $Time
#> 154 58 167 157 45 150 192 134 68 180 29 51 18
#> 12.63 19.34 15.55 15.10 17.42 20.33 16.44 17.81 20.62 14.82 15.45 18.23 15.21
#> 158 108 90 154.1 168 127 136 13 36 171 183 139 36.1
#> 20.14 18.29 20.94 12.63 23.72 3.53 21.83 14.34 21.19 16.57 9.24 21.49 21.19
#> 177 158.1 153 113 23 99 14 167.1 188 154.2 39 181 181.1
#> 12.53 20.14 21.33 22.86 16.92 21.19 12.89 15.55 16.16 12.63 15.59 16.46 16.46
#> 32 25 169 169.1 101 68.1 101.1 86 68.2 58.1 61 140 139.1
#> 20.90 6.32 22.41 22.41 9.97 20.62 9.97 23.81 20.62 19.34 10.12 12.68 21.49
#> 101.2 70 36.2 149 158.2 36.3 37 159 170 169.2 170.1 60 111
#> 9.97 7.38 21.19 8.37 20.14 21.19 12.52 10.55 19.54 22.41 19.54 13.15 17.45
#> 171.1 100 155 153.1 86.1 76 30 154.3 25.1 56 181.2 79 150.1
#> 16.57 16.07 13.08 21.33 23.81 19.22 17.43 12.63 6.32 12.21 16.46 16.23 20.33
#> 56.1 14.1 6 188.1 169.3 96 149.1 24 43 194 194.1 26 159.1
#> 12.21 12.89 15.64 16.16 22.41 14.54 8.37 23.89 12.10 22.40 22.40 15.77 10.55
#> 108.1 16 107 169.4 45.1 175 106 32.1 113.1 51.1 166 49 129
#> 18.29 8.71 11.18 22.41 17.42 21.91 16.67 20.90 22.86 18.23 19.98 12.19 23.41
#> 41 29.1 85 92 166.1 139.2 3 173 21 121 196 119 141
#> 18.02 15.45 16.44 22.92 19.98 21.49 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 104 141.1 137 31 53 20 75 46 146 31.1 35 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 82 119.1 174 126.1 185 95 144 11 35.1 12 143 196.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 174.1 87 11.1 193.1 47 142 84 151 47.1 132 27 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 186 67 44 54 144.1 46.1 9 186.1 118 174.2 28 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.2 200 48 84.1 17 200.1 44.1 135.1 65.1 182 185.1 34 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 118.1 132.1 144.2 137.2 174.3 44.2 22 3.1 3.2 109 20.1 75.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[27]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01791758 0.56842589 0.61465333
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.10514382 0.02293143 -0.30119288
#> grade_iii, Cure model
#> 0.97097199
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 30 17.43 1 78 0 0
#> 45 17.42 1 54 0 1
#> 129 23.41 1 53 1 0
#> 190 20.81 1 42 1 0
#> 99 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 68.1 20.62 1 44 0 0
#> 70 7.38 1 30 1 0
#> 199 19.81 1 NA 0 1
#> 124 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 57 14.46 1 45 0 1
#> 58 19.34 1 39 0 0
#> 39 15.59 1 37 0 1
#> 51 18.23 1 83 0 1
#> 25.1 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 51.1 18.23 1 83 0 1
#> 197 21.60 1 69 1 0
#> 175 21.91 1 43 0 0
#> 63 22.77 1 31 1 0
#> 76 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 150 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 170 19.54 1 43 0 1
#> 16 8.71 1 71 0 1
#> 107 11.18 1 54 1 0
#> 113.1 22.86 1 34 0 0
#> 16.1 8.71 1 71 0 1
#> 23 16.92 1 61 0 0
#> 105 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 110 17.56 1 65 0 1
#> 15 22.68 1 48 0 0
#> 26 15.77 1 49 0 1
#> 52 10.42 1 52 0 1
#> 26.1 15.77 1 49 0 1
#> 150.1 20.33 1 48 0 0
#> 8 18.43 1 32 0 0
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 194 22.40 1 38 0 1
#> 157 15.10 1 47 0 0
#> 14 12.89 1 21 0 0
#> 133 14.65 1 57 0 0
#> 55 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 183 9.24 1 67 1 0
#> 15.1 22.68 1 48 0 0
#> 24 23.89 1 38 0 0
#> 39.1 15.59 1 37 0 1
#> 136 21.83 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 106 16.67 1 49 1 0
#> 57.1 14.46 1 45 0 1
#> 192.1 16.44 1 31 1 0
#> 113.2 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 8.1 18.43 1 32 0 0
#> 159 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 88 18.37 1 47 0 0
#> 68.2 20.62 1 44 0 0
#> 26.2 15.77 1 49 0 1
#> 77.2 7.27 1 67 0 1
#> 61.1 10.12 1 36 0 1
#> 195.1 11.76 1 NA 1 0
#> 134 17.81 1 47 1 0
#> 188 16.16 1 46 0 1
#> 18 15.21 1 49 1 0
#> 13.1 14.34 1 54 0 1
#> 155 13.08 1 26 0 0
#> 188.1 16.16 1 46 0 1
#> 194.1 22.40 1 38 0 1
#> 130 16.47 1 53 0 1
#> 117 17.46 1 26 0 1
#> 41 18.02 1 40 1 0
#> 70.1 7.38 1 30 1 0
#> 23.1 16.92 1 61 0 0
#> 157.1 15.10 1 47 0 0
#> 68.3 20.62 1 44 0 0
#> 26.3 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 194.2 22.40 1 38 0 1
#> 127 3.53 1 62 0 1
#> 170.1 19.54 1 43 0 1
#> 125 15.65 1 67 1 0
#> 171 16.57 1 41 0 1
#> 30.1 17.43 1 78 0 0
#> 184 17.77 1 38 0 0
#> 91.1 5.33 1 61 0 1
#> 92 22.92 1 47 0 1
#> 77.3 7.27 1 67 0 1
#> 23.2 16.92 1 61 0 0
#> 153 21.33 1 55 1 0
#> 111.1 17.45 1 47 0 1
#> 133.1 14.65 1 57 0 0
#> 91.2 5.33 1 61 0 1
#> 107.1 11.18 1 54 1 0
#> 183.2 9.24 1 67 1 0
#> 149 8.37 1 33 1 0
#> 199.1 19.81 1 NA 0 1
#> 61.2 10.12 1 36 0 1
#> 167 15.55 1 56 1 0
#> 138 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 200 24.00 0 64 0 0
#> 80 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 87.1 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 116 24.00 0 58 0 1
#> 148 24.00 0 61 1 0
#> 80.1 24.00 0 41 0 0
#> 115 24.00 0 NA 1 0
#> 73 24.00 0 NA 0 1
#> 2 24.00 0 9 0 0
#> 53 24.00 0 32 0 1
#> 118 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 80.2 24.00 0 41 0 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 98.1 24.00 0 34 1 0
#> 94 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 182 24.00 0 35 0 0
#> 22.1 24.00 0 52 1 0
#> 119.1 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 44 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 74.1 24.00 0 43 0 1
#> 137.1 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 44.1 24.00 0 56 0 0
#> 146 24.00 0 63 1 0
#> 98.2 24.00 0 34 1 0
#> 138.1 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 138.2 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 94.1 24.00 0 51 0 1
#> 138.3 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 84 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 33 24.00 0 53 0 0
#> 147 24.00 0 76 1 0
#> 65.1 24.00 0 57 1 0
#> 116.1 24.00 0 58 0 1
#> 98.3 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 12 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 17.1 24.00 0 38 0 1
#> 148.1 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 71 24.00 0 51 0 0
#> 17.2 24.00 0 38 0 1
#> 118.1 24.00 0 44 1 0
#> 65.2 24.00 0 57 1 0
#> 35 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 34.1 24.00 0 36 0 0
#> 174 24.00 0 49 1 0
#> 12.1 24.00 0 63 0 0
#> 53.1 24.00 0 32 0 1
#> 72.1 24.00 0 40 0 1
#> 200.1 24.00 0 64 0 0
#> 138.4 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 7.1 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.11 NA NA NA
#> 2 age, Cure model 0.0229 NA NA NA
#> 3 grade_ii, Cure model -0.301 NA NA NA
#> 4 grade_iii, Cure model 0.971 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0179 NA NA NA
#> 2 grade_ii, Survival model 0.568 NA NA NA
#> 3 grade_iii, Survival model 0.615 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.10514 0.02293 -0.30119 0.97097
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 244.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.10514382 0.02293143 -0.30119288 0.97097199
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01791758 0.56842589 0.61465333
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9850241 0.7918389 0.8017567 0.2776981 0.6048236 0.5945398 0.6146485
#> [8] 0.6146485 0.9692139 0.9105481 0.9746927 0.9036329 0.6997249 0.8745521
#> [15] 0.7414550 0.9850241 0.9746927 0.7414550 0.5721859 0.5454268 0.4263672
#> [22] 0.7141007 0.6503439 0.6591537 0.3548842 0.6843414 0.9608616 0.9272815
#> [29] 0.3548842 0.9608616 0.8066146 0.6760441 0.8707185 0.7706366 0.4488918
#> [36] 0.8512317 0.9368966 0.8512317 0.6591537 0.7210533 0.9239761 0.5311474
#> [43] 0.4876479 0.8893611 0.9206238 0.8965474 0.6997249 0.8341781 0.9400401
#> [50] 0.9522278 0.4488918 0.1673952 0.8745521 0.5592850 0.9522278 0.8206024
#> [57] 0.9036329 0.8341781 0.3548842 0.7815278 0.7210533 0.9337137 0.9901430
#> [64] 0.7346887 0.6146485 0.8512317 0.9746927 0.9400401 0.7592315 0.8428436
#> [71] 0.8857217 0.9105481 0.9172660 0.8428436 0.4876479 0.8297380 0.7761194
#> [78] 0.7533713 0.9692139 0.8066146 0.8893611 0.6146485 0.8512317 0.9492076
#> [85] 0.4876479 0.9975522 0.6843414 0.8668678 0.8252063 0.7918389 0.7649548
#> [92] 0.9901430 0.3235859 0.9746927 0.8066146 0.5837614 0.7815278 0.8965474
#> [99] 0.9901430 0.9272815 0.9522278 0.9664388 0.9400401 0.8820330 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [190] 0.0000000
#>
#> $Time
#> 25 30 45 129 190 99 68 68.1 70 13 77 57 58
#> 6.32 17.43 17.42 23.41 20.81 21.19 20.62 20.62 7.38 14.34 7.27 14.46 19.34
#> 39 51 25.1 77.1 51.1 197 175 63 76 128 150 113 170
#> 15.59 18.23 6.32 7.27 18.23 21.60 21.91 22.77 19.22 20.35 20.33 22.86 19.54
#> 16 107 113.1 16.1 23 105 6 110 15 26 52 26.1 150.1
#> 8.71 11.18 22.86 8.71 16.92 19.75 15.64 17.56 22.68 15.77 10.42 15.77 20.33
#> 8 37 66 194 157 14 133 55 192 61 183 15.1 24
#> 18.43 12.52 22.13 22.40 15.10 12.89 14.65 19.34 16.44 10.12 9.24 22.68 23.89
#> 39.1 136 183.1 106 57.1 192.1 113.2 111 8.1 159 91 88 68.2
#> 15.59 21.83 9.24 16.67 14.46 16.44 22.86 17.45 18.43 10.55 5.33 18.37 20.62
#> 26.2 77.2 61.1 134 188 18 13.1 155 188.1 194.1 130 117 41
#> 15.77 7.27 10.12 17.81 16.16 15.21 14.34 13.08 16.16 22.40 16.47 17.46 18.02
#> 70.1 23.1 157.1 68.3 26.3 145 194.2 127 170.1 125 171 30.1 184
#> 7.38 16.92 15.10 20.62 15.77 10.07 22.40 3.53 19.54 15.65 16.57 17.43 17.77
#> 91.1 92 77.3 23.2 153 111.1 133.1 91.2 107.1 183.2 149 61.2 167
#> 5.33 22.92 7.27 16.92 21.33 17.45 14.65 5.33 11.18 9.24 8.37 10.12 15.55
#> 138 21 34 200 80 121 87 137 165 72 87.1 46 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 80.1 2 53 118 98 80.2 156 22 98.1 94 17 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 74 182 22.1 119.1 193 44 142 74.1 137.1 47 44.1 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.2 138.1 156.1 138.2 65 94.1 138.3 67 173 84 109 33 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 116.1 98.3 172 122 33.1 12 151 160 135 17.1 148.1 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 162 71 17.2 118.1 65.2 35 141 146.1 1 34.1 174 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 72.1 200.1 138.4 176 9 161 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[28]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02025531 0.52603755 0.23064860
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74469736 0.01345559 -0.06581820
#> grade_iii, Cure model
#> 1.11782800
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 153 21.33 1 55 1 0
#> 123 13.00 1 44 1 0
#> 164 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 167 15.55 1 56 1 0
#> 125 15.65 1 67 1 0
#> 168 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 168.1 23.72 1 70 0 0
#> 15 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 111 17.45 1 47 0 1
#> 36 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 189 10.51 1 NA 1 0
#> 150 20.33 1 48 0 0
#> 181 16.46 1 45 0 1
#> 110 17.56 1 65 0 1
#> 5 16.43 1 51 0 1
#> 58 19.34 1 39 0 0
#> 145 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 93 10.33 1 52 0 1
#> 136 21.83 1 43 0 1
#> 97 19.14 1 65 0 1
#> 86 23.81 1 58 0 1
#> 136.1 21.83 1 43 0 1
#> 188 16.16 1 46 0 1
#> 76 19.22 1 54 0 1
#> 164.1 23.60 1 76 0 1
#> 184 17.77 1 38 0 0
#> 199 19.81 1 NA 0 1
#> 5.1 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 85 16.44 1 36 0 0
#> 25 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 91 5.33 1 61 0 1
#> 78 23.88 1 43 0 0
#> 101 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 32 20.90 1 37 1 0
#> 145.1 10.07 1 65 1 0
#> 92 22.92 1 47 0 1
#> 50 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 85.1 16.44 1 36 0 0
#> 149 8.37 1 33 1 0
#> 23 16.92 1 61 0 0
#> 155 13.08 1 26 0 0
#> 25.1 6.32 1 34 1 0
#> 99 21.19 1 38 0 1
#> 155.1 13.08 1 26 0 0
#> 99.1 21.19 1 38 0 1
#> 168.2 23.72 1 70 0 0
#> 26 15.77 1 49 0 1
#> 91.1 5.33 1 61 0 1
#> 36.1 21.19 1 48 0 1
#> 150.1 20.33 1 48 0 0
#> 155.2 13.08 1 26 0 0
#> 90 20.94 1 50 0 1
#> 63 22.77 1 31 1 0
#> 76.1 19.22 1 54 0 1
#> 127 3.53 1 62 0 1
#> 139 21.49 1 63 1 0
#> 29 15.45 1 68 1 0
#> 91.2 5.33 1 61 0 1
#> 79 16.23 1 54 1 0
#> 190 20.81 1 42 1 0
#> 26.1 15.77 1 49 0 1
#> 127.1 3.53 1 62 0 1
#> 49 12.19 1 48 1 0
#> 188.1 16.16 1 46 0 1
#> 5.2 16.43 1 51 0 1
#> 61 10.12 1 36 0 1
#> 93.1 10.33 1 52 0 1
#> 86.1 23.81 1 58 0 1
#> 66 22.13 1 53 0 0
#> 58.1 19.34 1 39 0 0
#> 123.1 13.00 1 44 1 0
#> 6 15.64 1 39 0 0
#> 150.2 20.33 1 48 0 0
#> 39 15.59 1 37 0 1
#> 89 11.44 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 52 10.42 1 52 0 1
#> 113 22.86 1 34 0 0
#> 49.1 12.19 1 48 1 0
#> 149.1 8.37 1 33 1 0
#> 43 12.10 1 61 0 1
#> 111.1 17.45 1 47 0 1
#> 4 17.64 1 NA 0 1
#> 164.2 23.60 1 76 0 1
#> 85.2 16.44 1 36 0 0
#> 41 18.02 1 40 1 0
#> 180 14.82 1 37 0 0
#> 164.3 23.60 1 76 0 1
#> 170.1 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 61.1 10.12 1 36 0 1
#> 6.1 15.64 1 39 0 0
#> 179 18.63 1 42 0 0
#> 105.1 19.75 1 60 0 0
#> 140 12.68 1 59 1 0
#> 197 21.60 1 69 1 0
#> 59 10.16 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 13 14.34 1 54 0 1
#> 56 12.21 1 60 0 0
#> 40 18.00 1 28 1 0
#> 10.1 10.53 1 34 0 0
#> 112 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 165 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 67 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 7 24.00 0 37 1 0
#> 160 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 182 24.00 0 35 0 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 120.1 24.00 0 68 0 1
#> 126 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 120.2 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 1 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 87.1 24.00 0 27 0 0
#> 104.1 24.00 0 50 1 0
#> 72 24.00 0 40 0 1
#> 33 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 141 24.00 0 44 1 0
#> 176 24.00 0 43 0 1
#> 35.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 1.1 24.00 0 23 1 0
#> 34.1 24.00 0 36 0 0
#> 172 24.00 0 41 0 0
#> 74.1 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 186 24.00 0 45 1 0
#> 151 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 148 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 132 24.00 0 55 0 0
#> 94.1 24.00 0 51 0 1
#> 1.2 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 54.1 24.00 0 53 1 0
#> 196 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 54.2 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 22 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 7.2 24.00 0 37 1 0
#> 131.1 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 160.1 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 163 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 173 24.00 0 19 0 1
#> 174.1 24.00 0 49 1 0
#> 131.2 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 33.1 24.00 0 53 0 0
#> 94.2 24.00 0 51 0 1
#> 64 24.00 0 43 0 0
#> 132.1 24.00 0 55 0 0
#> 163.1 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 104.2 24.00 0 50 1 0
#> 122.1 24.00 0 66 0 0
#> 132.2 24.00 0 55 0 0
#> 146 24.00 0 63 1 0
#> 20 24.00 0 46 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.745 NA NA NA
#> 2 age, Cure model 0.0135 NA NA NA
#> 3 grade_ii, Cure model -0.0658 NA NA NA
#> 4 grade_iii, Cure model 1.12 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0203 NA NA NA
#> 2 grade_ii, Survival model 0.526 NA NA NA
#> 3 grade_iii, Survival model 0.231 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74470 0.01346 -0.06582 1.11783
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 248.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74469736 0.01345559 -0.06581820 1.11782800
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02025531 0.52603755 0.23064860
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.530752e-02 5.321251e-01 1.242658e-03 6.368124e-01 4.357708e-01
#> [6] 3.848002e-01 2.611623e-04 2.437614e-01 2.611623e-04 9.876615e-03
#> [11] 8.358700e-02 7.298305e-02 1.802877e-01 2.862613e-02 9.486882e-02
#> [16] 5.903937e-02 2.339795e-01 1.721029e-01 2.830523e-01 9.486882e-02
#> [21] 7.509388e-01 2.243956e-01 6.845886e-01 1.426598e-02 1.265687e-01
#> [26] 4.909104e-05 1.426598e-02 3.261055e-01 1.131597e-01 1.242658e-03
#> [31] 1.641682e-01 2.830523e-01 8.546835e-01 2.437614e-01 8.724448e-01
#> [36] 1.410948e-01 9.078200e-01 4.501585e-06 7.852509e-01 8.025877e-01
#> [41] 4.646322e-02 7.509388e-01 4.706147e-03 1.970506e-01 2.437614e-01
#> [46] 8.200119e-01 2.059246e-01 4.901116e-01 8.724448e-01 2.862613e-02
#> [51] 4.901116e-01 2.862613e-02 2.611623e-04 3.606831e-01 9.078200e-01
#> [56] 2.862613e-02 5.903937e-02 4.901116e-01 4.231479e-02 8.051787e-03
#> [61] 1.131597e-01 9.623641e-01 2.217201e-02 4.490219e-01 9.078200e-01
#> [66] 3.149302e-01 5.467292e-02 3.606831e-01 9.623641e-01 5.908808e-01
#> [71] 3.261055e-01 2.830523e-01 7.174625e-01 6.845886e-01 4.909104e-05
#> [76] 1.193881e-02 9.486882e-02 5.321251e-01 3.972781e-01 5.903937e-02
#> [81] 4.227008e-01 2.059246e-01 6.683911e-01 6.267676e-03 5.908808e-01
#> [86] 8.200119e-01 6.212124e-01 1.802877e-01 1.242658e-03 2.437614e-01
#> [91] 1.487155e-01 4.625011e-01 1.242658e-03 8.358700e-02 3.488455e-01
#> [96] 7.174625e-01 3.972781e-01 1.337187e-01 7.298305e-02 5.609877e-01
#> [101] 1.925451e-02 4.646322e-02 4.761906e-01 5.757978e-01 1.564341e-01
#> [106] 6.368124e-01 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 153 123 164 10 167 125 168 192 168.1 15 170 105 111
#> 21.33 13.00 23.60 10.53 15.55 15.65 23.72 16.44 23.72 22.68 19.54 19.75 17.45
#> 36 55 150 181 110 5 58 145 106 93 136 97 86
#> 21.19 19.34 20.33 16.46 17.56 16.43 19.34 10.07 16.67 10.33 21.83 19.14 23.81
#> 136.1 188 76 164.1 184 5.1 77 85 25 88 91 78 101
#> 21.83 16.16 19.22 23.60 17.77 16.43 7.27 16.44 6.32 18.37 5.33 23.88 9.97
#> 187 32 145.1 92 30 85.1 149 23 155 25.1 99 155.1 99.1
#> 9.92 20.90 10.07 22.92 17.43 16.44 8.37 16.92 13.08 6.32 21.19 13.08 21.19
#> 168.2 26 91.1 36.1 150.1 155.2 90 63 76.1 127 139 29 91.2
#> 23.72 15.77 5.33 21.19 20.33 13.08 20.94 22.77 19.22 3.53 21.49 15.45 5.33
#> 79 190 26.1 127.1 49 188.1 5.2 61 93.1 86.1 66 58.1 123.1
#> 16.23 20.81 15.77 3.53 12.19 16.16 16.43 10.12 10.33 23.81 22.13 19.34 13.00
#> 6 150.2 39 23.1 52 113 49.1 149.1 43 111.1 164.2 85.2 41
#> 15.64 20.33 15.59 16.92 10.42 22.86 12.19 8.37 12.10 17.45 23.60 16.44 18.02
#> 180 164.3 170.1 100 61.1 6.1 179 105.1 140 197 32.1 13 56
#> 14.82 23.60 19.54 16.07 10.12 15.64 18.63 19.75 12.68 21.60 20.90 14.34 12.21
#> 40 10.1 112 80 165 174 67 2 7 160 65 104 143
#> 18.00 10.53 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 116 94 182 74 120 120.1 126 118 87 35 120.2 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 1 28 87.1 104.1 72 33 54 34 141 176 35.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102.1 1.1 34.1 172 74.1 75 186 151 21 148 83 132 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.2 138 7.1 54.1 196 200 54.2 22 48 131 7.2 131.1 48.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 135 160.1 17 142 53 163 19 173 174.1 131.2 22.1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 64 132.1 163.1 122 104.2 122.1 132.2 146 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[29]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01003526 0.61728238 0.39500034
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.17243064 0.02343274 0.15353045
#> grade_iii, Cure model
#> 0.75720866
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 5 16.43 1 51 0 1
#> 101 9.97 1 10 0 1
#> 183 9.24 1 67 1 0
#> 105 19.75 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 168 23.72 1 70 0 0
#> 169 22.41 1 46 0 0
#> 113 22.86 1 34 0 0
#> 15 22.68 1 48 0 0
#> 58 19.34 1 39 0 0
#> 6 15.64 1 39 0 0
#> 194 22.40 1 38 0 1
#> 140 12.68 1 59 1 0
#> 159 10.55 1 50 0 1
#> 170 19.54 1 43 0 1
#> 25 6.32 1 34 1 0
#> 169.1 22.41 1 46 0 0
#> 108 18.29 1 39 0 1
#> 150 20.33 1 48 0 0
#> 187 9.92 1 39 1 0
#> 130 16.47 1 53 0 1
#> 111 17.45 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 157 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 25.1 6.32 1 34 1 0
#> 45 17.42 1 54 0 1
#> 164 23.60 1 76 0 1
#> 190 20.81 1 42 1 0
#> 30 17.43 1 78 0 0
#> 5.1 16.43 1 51 0 1
#> 129 23.41 1 53 1 0
#> 158 20.14 1 74 1 0
#> 125 15.65 1 67 1 0
#> 127 3.53 1 62 0 1
#> 55 19.34 1 69 0 1
#> 124 9.73 1 NA 1 0
#> 183.1 9.24 1 67 1 0
#> 159.1 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 68 20.62 1 44 0 0
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 37 12.52 1 57 1 0
#> 70 7.38 1 30 1 0
#> 68.1 20.62 1 44 0 0
#> 181 16.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 171 16.57 1 41 0 1
#> 15.1 22.68 1 48 0 0
#> 39 15.59 1 37 0 1
#> 6.1 15.64 1 39 0 0
#> 5.2 16.43 1 51 0 1
#> 49 12.19 1 48 1 0
#> 40 18.00 1 28 1 0
#> 5.3 16.43 1 51 0 1
#> 24 23.89 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 56 12.21 1 60 0 0
#> 14 12.89 1 21 0 0
#> 164.1 23.60 1 76 0 1
#> 5.4 16.43 1 51 0 1
#> 37.1 12.52 1 57 1 0
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 50 10.02 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 190.1 20.81 1 42 1 0
#> 23 16.92 1 61 0 0
#> 199 19.81 1 NA 0 1
#> 45.1 17.42 1 54 0 1
#> 40.1 18.00 1 28 1 0
#> 49.1 12.19 1 48 1 0
#> 177 12.53 1 75 0 0
#> 8 18.43 1 32 0 0
#> 123.1 13.00 1 44 1 0
#> 117 17.46 1 26 0 1
#> 30.1 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 187.1 9.92 1 39 1 0
#> 30.2 17.43 1 78 0 0
#> 159.2 10.55 1 50 0 1
#> 101.1 9.97 1 10 0 1
#> 157.1 15.10 1 47 0 0
#> 88 18.37 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 100 16.07 1 60 0 0
#> 43 12.10 1 61 0 1
#> 195.1 11.76 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 164.2 23.60 1 76 0 1
#> 97 19.14 1 65 0 1
#> 129.1 23.41 1 53 1 0
#> 154 12.63 1 20 1 0
#> 49.2 12.19 1 48 1 0
#> 166.1 19.98 1 48 0 0
#> 40.2 18.00 1 28 1 0
#> 127.1 3.53 1 62 0 1
#> 6.2 15.64 1 39 0 0
#> 134 17.81 1 47 1 0
#> 170.1 19.54 1 43 0 1
#> 29 15.45 1 68 1 0
#> 56.1 12.21 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 164.3 23.60 1 76 0 1
#> 136 21.83 1 43 0 1
#> 6.3 15.64 1 39 0 0
#> 199.1 19.81 1 NA 0 1
#> 29.1 15.45 1 68 1 0
#> 97.1 19.14 1 65 0 1
#> 197 21.60 1 69 1 0
#> 44 24.00 0 56 0 0
#> 186 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 3 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 44.1 24.00 0 56 0 0
#> 135 24.00 0 58 1 0
#> 98 24.00 0 34 1 0
#> 172 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 138 24.00 0 44 1 0
#> 178 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 3.1 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 31 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 142 24.00 0 53 0 0
#> 44.2 24.00 0 56 0 0
#> 94 24.00 0 51 0 1
#> 137 24.00 0 45 1 0
#> 165 24.00 0 47 0 0
#> 182 24.00 0 35 0 0
#> 135.1 24.00 0 58 1 0
#> 33 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 12.1 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 144.1 24.00 0 28 0 1
#> 103 24.00 0 56 1 0
#> 11 24.00 0 42 0 1
#> 1 24.00 0 23 1 0
#> 44.3 24.00 0 56 0 0
#> 131 24.00 0 66 0 0
#> 137.1 24.00 0 45 1 0
#> 131.1 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 38 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 87 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#> 2.1 24.00 0 9 0 0
#> 200.1 24.00 0 64 0 0
#> 151 24.00 0 42 0 0
#> 186.1 24.00 0 45 1 0
#> 12.2 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 131.2 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 62 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 174.2 24.00 0 49 1 0
#> 152 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 160 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 72 24.00 0 40 0 1
#> 94.1 24.00 0 51 0 1
#> 141 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 94.2 24.00 0 51 0 1
#> 115 24.00 0 NA 1 0
#> 172.1 24.00 0 41 0 0
#> 34.1 24.00 0 36 0 0
#> 65.1 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 198 24.00 0 66 0 1
#> 102 24.00 0 49 0 0
#> 22.1 24.00 0 52 1 0
#> 19 24.00 0 57 0 1
#> 152.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 9 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 34.2 24.00 0 36 0 0
#> 38.1 24.00 0 31 1 0
#> 72.2 24.00 0 40 0 1
#> 44.4 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 126 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 200.2 24.00 0 64 0 0
#> 82.1 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.17 NA NA NA
#> 2 age, Cure model 0.0234 NA NA NA
#> 3 grade_ii, Cure model 0.154 NA NA NA
#> 4 grade_iii, Cure model 0.757 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0100 NA NA NA
#> 2 grade_ii, Survival model 0.617 NA NA NA
#> 3 grade_iii, Survival model 0.395 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.17243 0.02343 0.15353 0.75721
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 254.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.17243064 0.02343274 0.15353045 0.75720866
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01003526 0.61728238 0.39500034
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.457918952 0.881600387 0.924839511 0.189672934 0.009711977 0.082397312
#> [7] 0.052888237 0.067612901 0.216688751 0.548816134 0.098237789 0.697410127
#> [13] 0.827071987 0.198798304 0.957227113 0.082397312 0.292116473 0.155063639
#> [19] 0.903285509 0.437525111 0.358585244 0.216688751 0.622148735 0.060410451
#> [25] 0.957227113 0.397361687 0.016620426 0.123105336 0.368163196 0.457918952
#> [31] 0.039426953 0.163621019 0.538395322 0.978566055 0.216688751 0.924839511
#> [37] 0.827071987 0.527985315 0.138755537 0.643594825 0.859598427 0.740458029
#> [43] 0.946420489 0.138755537 0.447715639 0.172231535 0.427364864 0.067612901
#> [49] 0.590320322 0.548816134 0.457918952 0.783820660 0.302075933 0.457918952
#> [55] 0.002245919 0.002245919 0.761999812 0.686625255 0.016620426 0.457918952
#> [61] 0.740458029 0.654465374 0.870597015 0.665288093 0.123105336 0.417208566
#> [67] 0.397361687 0.302075933 0.783820660 0.718887230 0.262828867 0.665288093
#> [73] 0.349026148 0.368163196 0.507296609 0.903285509 0.368163196 0.827071987
#> [79] 0.881600387 0.622148735 0.272534793 0.718887230 0.517594203 0.816128739
#> [85] 0.339429358 0.016620426 0.243963256 0.039426953 0.708190748 0.783820660
#> [91] 0.172231535 0.302075933 0.978566055 0.548816134 0.329917842 0.198798304
#> [97] 0.600977122 0.761999812 0.272534793 0.016620426 0.106496829 0.548816134
#> [103] 0.600977122 0.243963256 0.114779213 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 5 101 183 105 168 169 113 15 58 6 194 140 159
#> 16.43 9.97 9.24 19.75 23.72 22.41 22.86 22.68 19.34 15.64 22.40 12.68 10.55
#> 170 25 169.1 108 150 187 130 111 58.1 157 63 25.1 45
#> 19.54 6.32 22.41 18.29 20.33 9.92 16.47 17.45 19.34 15.10 22.77 6.32 17.42
#> 164 190 30 5.1 129 158 125 127 55 183.1 159.1 26 68
#> 23.60 20.81 17.43 16.43 23.41 20.14 15.65 3.53 19.34 9.24 10.55 15.77 20.62
#> 180 93 37 70 68.1 181 166 171 15.1 39 6.1 5.2 49
#> 14.82 10.33 12.52 7.38 20.62 16.46 19.98 16.57 22.68 15.59 15.64 16.43 12.19
#> 40 5.3 24 24.1 56 14 164.1 5.4 37.1 60 145 123 190.1
#> 18.00 16.43 23.89 23.89 12.21 12.89 23.60 16.43 12.52 13.15 10.07 13.00 20.81
#> 23 45.1 40.1 49.1 177 8 123.1 117 30.1 188 187.1 30.2 159.2
#> 16.92 17.42 18.00 12.19 12.53 18.43 13.00 17.46 17.43 16.16 9.92 17.43 10.55
#> 101.1 157.1 88 177.1 100 43 184 164.2 97 129.1 154 49.2 166.1
#> 9.97 15.10 18.37 12.53 16.07 12.10 17.77 23.60 19.14 23.41 12.63 12.19 19.98
#> 40.2 127.1 6.2 134 170.1 29 56.1 88.1 164.3 136 6.3 29.1 97.1
#> 18.00 3.53 15.64 17.81 19.54 15.45 12.21 18.37 23.60 21.83 15.64 15.45 19.14
#> 197 44 186 118 2 3 22 12 44.1 135 98 172 82
#> 21.60 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 178 65 3.1 21 64 31 67 142 44.2 94 137 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 135.1 33 200 12.1 144 144.1 103 11 1 44.3 131 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 11.1 38 119 87 103.1 2.1 200.1 151 186.1 12.2 193 131.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 62 174.1 34 174.2 152 109 160 84 72 94.1 141 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 172.1 34.1 65.1 178.1 198 102 22.1 19 152.1 83 9 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 38.1 72.2 44.4 176 126 20 200.2 82.1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[30]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01783979 0.61286580 -0.06019371
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.283601693 0.005446222 -0.096233244
#> grade_iii, Cure model
#> 1.095855147
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 166 19.98 1 48 0 0
#> 63 22.77 1 31 1 0
#> 59 10.16 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 99 21.19 1 38 0 1
#> 111 17.45 1 47 0 1
#> 86 23.81 1 58 0 1
#> 61 10.12 1 36 0 1
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 13 14.34 1 54 0 1
#> 188 16.16 1 46 0 1
#> 188.1 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 192.1 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 150 20.33 1 48 0 0
#> 6 15.64 1 39 0 0
#> 90 20.94 1 50 0 1
#> 96 14.54 1 33 0 1
#> 157.1 15.10 1 47 0 0
#> 183.1 9.24 1 67 1 0
#> 197 21.60 1 69 1 0
#> 59.1 10.16 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 105 19.75 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 188.2 16.16 1 46 0 1
#> 158.1 20.14 1 74 1 0
#> 99.1 21.19 1 38 0 1
#> 175 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 177 12.53 1 75 0 0
#> 108 18.29 1 39 0 1
#> 99.2 21.19 1 38 0 1
#> 88 18.37 1 47 0 0
#> 81 14.06 1 34 0 0
#> 123 13.00 1 44 1 0
#> 96.1 14.54 1 33 0 1
#> 37 12.52 1 57 1 0
#> 40 18.00 1 28 1 0
#> 13.1 14.34 1 54 0 1
#> 57 14.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 18 15.21 1 49 1 0
#> 79 16.23 1 54 1 0
#> 96.2 14.54 1 33 0 1
#> 108.1 18.29 1 39 0 1
#> 79.1 16.23 1 54 1 0
#> 168 23.72 1 70 0 0
#> 105.1 19.75 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 157.2 15.10 1 47 0 0
#> 111.1 17.45 1 47 0 1
#> 140 12.68 1 59 1 0
#> 23 16.92 1 61 0 0
#> 157.3 15.10 1 47 0 0
#> 167 15.55 1 56 1 0
#> 42 12.43 1 49 0 1
#> 43 12.10 1 61 0 1
#> 59.2 10.16 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 79.2 16.23 1 54 1 0
#> 188.3 16.16 1 46 0 1
#> 101 9.97 1 10 0 1
#> 76 19.22 1 54 0 1
#> 81.1 14.06 1 34 0 0
#> 58 19.34 1 39 0 0
#> 150.1 20.33 1 48 0 0
#> 79.3 16.23 1 54 1 0
#> 6.1 15.64 1 39 0 0
#> 105.2 19.75 1 60 0 0
#> 164.1 23.60 1 76 0 1
#> 92 22.92 1 47 0 1
#> 169 22.41 1 46 0 0
#> 79.4 16.23 1 54 1 0
#> 105.3 19.75 1 60 0 0
#> 192.2 16.44 1 31 1 0
#> 37.1 12.52 1 57 1 0
#> 51 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 157.4 15.10 1 47 0 0
#> 155 13.08 1 26 0 0
#> 6.2 15.64 1 39 0 0
#> 79.5 16.23 1 54 1 0
#> 6.3 15.64 1 39 0 0
#> 100 16.07 1 60 0 0
#> 154.1 12.63 1 20 1 0
#> 93 10.33 1 52 0 1
#> 86.1 23.81 1 58 0 1
#> 145 10.07 1 65 1 0
#> 41 18.02 1 40 1 0
#> 70 7.38 1 30 1 0
#> 29.1 15.45 1 68 1 0
#> 113 22.86 1 34 0 0
#> 167.1 15.55 1 56 1 0
#> 181 16.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 99.3 21.19 1 38 0 1
#> 91 5.33 1 61 0 1
#> 168.2 23.72 1 70 0 0
#> 18.1 15.21 1 49 1 0
#> 154.2 12.63 1 20 1 0
#> 10.1 10.53 1 34 0 0
#> 184 17.77 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 58.1 19.34 1 39 0 0
#> 148 24.00 0 61 1 0
#> 148.1 24.00 0 61 1 0
#> 65 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 131 24.00 0 66 0 0
#> 73 24.00 0 NA 0 1
#> 83 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 135 24.00 0 58 1 0
#> 142 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 54.1 24.00 0 53 1 0
#> 198 24.00 0 66 0 1
#> 1 24.00 0 23 1 0
#> 65.1 24.00 0 57 1 0
#> 196 24.00 0 19 0 0
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 64.1 24.00 0 43 0 0
#> 193 24.00 0 45 0 1
#> 12.1 24.00 0 63 0 0
#> 31 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 48 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 104.1 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 104.2 24.00 0 50 1 0
#> 137 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 1.1 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 47 24.00 0 38 0 1
#> 165 24.00 0 47 0 0
#> 112 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 104.3 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 162 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 152 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 198.1 24.00 0 66 0 1
#> 112.1 24.00 0 61 0 0
#> 135.1 24.00 0 58 1 0
#> 19 24.00 0 57 0 1
#> 1.2 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 28.1 24.00 0 67 1 0
#> 178 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 131.1 24.00 0 66 0 0
#> 65.2 24.00 0 57 1 0
#> 163 24.00 0 66 0 0
#> 144 24.00 0 28 0 1
#> 109 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 9 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 21 24.00 0 47 0 0
#> 87.1 24.00 0 27 0 0
#> 176 24.00 0 43 0 1
#> 20 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 126 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 35 24.00 0 51 0 0
#> 131.2 24.00 0 66 0 0
#> 126.1 24.00 0 48 0 0
#> 65.3 24.00 0 57 1 0
#> 196.2 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 160.1 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.284 NA NA NA
#> 2 age, Cure model 0.00545 NA NA NA
#> 3 grade_ii, Cure model -0.0962 NA NA NA
#> 4 grade_iii, Cure model 1.10 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0178 NA NA NA
#> 2 grade_ii, Survival model 0.613 NA NA NA
#> 3 grade_iii, Survival model -0.0602 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.283602 0.005446 -0.096233 1.095855
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 252.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.283601693 0.005446222 -0.096233244 1.095855147
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01783979 0.61286580 -0.06019371
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 4.429403e-02 7.386006e-03 3.641348e-02 1.576621e-02 1.514095e-01
#> [6] 7.185690e-06 8.489244e-01 1.771249e-01 4.445810e-01 9.151823e-01
#> [11] 1.958272e-01 5.759359e-01 2.768995e-01 2.768995e-01 9.826976e-01
#> [16] 1.958272e-01 8.008273e-01 2.931456e-02 3.284715e-01 2.601458e-02
#> [21] 5.076272e-01 4.445810e-01 9.151823e-01 1.337341e-02 6.798913e-01
#> [26] 5.307529e-02 3.962472e-01 2.768995e-01 3.641348e-02 1.576621e-02
#> [31] 1.116344e-02 8.985332e-01 1.014493e-03 7.238213e-01 1.051011e-01
#> [36] 1.576621e-02 9.810359e-02 6.048472e-01 6.494862e-01 5.076272e-01
#> [41] 7.390026e-01 1.354384e-01 5.759359e-01 5.479256e-01 2.737143e-03
#> [46] 4.202542e-01 2.227079e-01 5.076272e-01 1.051011e-01 2.227079e-01
#> [51] 1.427336e-04 5.307529e-02 4.429403e-02 4.445810e-01 1.514095e-01
#> [56] 6.646269e-01 1.682038e-01 4.445810e-01 3.728794e-01 7.694651e-01
#> [61] 7.850392e-01 5.479256e-01 2.227079e-01 2.768995e-01 8.819086e-01
#> [66] 8.498498e-02 6.048472e-01 7.322390e-02 2.931456e-02 2.227079e-01
#> [71] 3.284715e-01 5.307529e-02 1.014493e-03 4.010466e-03 9.165841e-03
#> [76] 2.227079e-01 5.307529e-02 1.958272e-01 7.390026e-01 1.196231e-01
#> [81] 9.137846e-02 4.445810e-01 6.344010e-01 3.284715e-01 2.227079e-01
#> [86] 3.284715e-01 3.175416e-01 6.798913e-01 8.326572e-01 7.185690e-06
#> [91] 8.653503e-01 1.275072e-01 9.487114e-01 3.962472e-01 5.581681e-03
#> [96] 3.728794e-01 1.863404e-01 1.427336e-04 1.576621e-02 9.656024e-01
#> [101] 1.427336e-04 4.202542e-01 6.798913e-01 8.008273e-01 1.433144e-01
#> [106] 7.322390e-02 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00
#>
#> $Time
#> 166 63 158 99 111 86 61 130 157 183 192 13 188
#> 19.98 22.77 20.14 21.19 17.45 23.81 10.12 16.47 15.10 9.24 16.44 14.34 16.16
#> 188.1 127 192.1 10 150 6 90 96 157.1 183.1 197 154 105
#> 16.16 3.53 16.44 10.53 20.33 15.64 20.94 14.54 15.10 9.24 21.60 12.63 19.75
#> 29 188.2 158.1 99.1 175 187 164 177 108 99.2 88 81 123
#> 15.45 16.16 20.14 21.19 21.91 9.92 23.60 12.53 18.29 21.19 18.37 14.06 13.00
#> 96.1 37 40 13.1 57 69 18 79 96.2 108.1 79.1 168 105.1
#> 14.54 12.52 18.00 14.34 14.46 23.23 15.21 16.23 14.54 18.29 16.23 23.72 19.75
#> 166.1 157.2 111.1 140 23 157.3 167 42 43 57.1 79.2 188.3 101
#> 19.98 15.10 17.45 12.68 16.92 15.10 15.55 12.43 12.10 14.46 16.23 16.16 9.97
#> 76 81.1 58 150.1 79.3 6.1 105.2 164.1 92 169 79.4 105.3 192.2
#> 19.22 14.06 19.34 20.33 16.23 15.64 19.75 23.60 22.92 22.41 16.23 19.75 16.44
#> 37.1 51 97 157.4 155 6.2 79.5 6.3 100 154.1 93 86.1 145
#> 12.52 18.23 19.14 15.10 13.08 15.64 16.23 15.64 16.07 12.63 10.33 23.81 10.07
#> 41 70 29.1 113 167.1 181 168.1 99.3 91 168.2 18.1 154.2 10.1
#> 18.02 7.38 15.45 22.86 15.55 16.46 23.72 21.19 5.33 23.72 15.21 12.63 10.53
#> 184 58.1 148 148.1 65 87 46 131 83 7 135 142 54
#> 17.77 19.34 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 84 54.1 198 1 65.1 196 64 12 64.1 193 12.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 48 141 138 48.1 64.2 104.1 71 151 146 104.2 137 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1.1 95 28 67 47 165 112 116 104.3 2 162 200 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160 193.1 198.1 112.1 135.1 19 1.2 119 28.1 178 196.1 131.1 65.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 144 109 137.1 118 147 9 21 87.1 176 20 156 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 44 35 131.2 126.1 65.3 196.2 121 160.1 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[31]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005268463 0.876183500 0.331560764
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.26961012 0.01028464 -0.21250650
#> grade_iii, Cure model
#> 0.20039579
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 179 18.63 1 42 0 0
#> 79 16.23 1 54 1 0
#> 92 22.92 1 47 0 1
#> 113 22.86 1 34 0 0
#> 10 10.53 1 34 0 0
#> 105 19.75 1 60 0 0
#> 168 23.72 1 70 0 0
#> 43 12.10 1 61 0 1
#> 51 18.23 1 83 0 1
#> 113.1 22.86 1 34 0 0
#> 184 17.77 1 38 0 0
#> 39 15.59 1 37 0 1
#> 79.1 16.23 1 54 1 0
#> 190 20.81 1 42 1 0
#> 194 22.40 1 38 0 1
#> 140 12.68 1 59 1 0
#> 164 23.60 1 76 0 1
#> 180 14.82 1 37 0 0
#> 167 15.55 1 56 1 0
#> 39.1 15.59 1 37 0 1
#> 10.1 10.53 1 34 0 0
#> 107 11.18 1 54 1 0
#> 15 22.68 1 48 0 0
#> 107.1 11.18 1 54 1 0
#> 100 16.07 1 60 0 0
#> 37 12.52 1 57 1 0
#> 175 21.91 1 43 0 0
#> 199 19.81 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 188 16.16 1 46 0 1
#> 130 16.47 1 53 0 1
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 78 23.88 1 43 0 0
#> 70 7.38 1 30 1 0
#> 155 13.08 1 26 0 0
#> 68 20.62 1 44 0 0
#> 39.2 15.59 1 37 0 1
#> 155.1 13.08 1 26 0 0
#> 184.1 17.77 1 38 0 0
#> 45.1 17.42 1 54 0 1
#> 29 15.45 1 68 1 0
#> 136 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 187 9.92 1 39 1 0
#> 97 19.14 1 65 0 1
#> 69 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 113.2 22.86 1 34 0 0
#> 45.2 17.42 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 10.2 10.53 1 34 0 0
#> 133 14.65 1 57 0 0
#> 130.1 16.47 1 53 0 1
#> 50.1 10.02 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 140.1 12.68 1 59 1 0
#> 88 18.37 1 47 0 0
#> 194.1 22.40 1 38 0 1
#> 24 23.89 1 38 0 0
#> 92.1 22.92 1 47 0 1
#> 184.2 17.77 1 38 0 0
#> 88.1 18.37 1 47 0 0
#> 23 16.92 1 61 0 0
#> 60.1 13.15 1 38 1 0
#> 157 15.10 1 47 0 0
#> 133.1 14.65 1 57 0 0
#> 157.1 15.10 1 47 0 0
#> 61 10.12 1 36 0 1
#> 50.2 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 184.3 17.77 1 38 0 0
#> 78.1 23.88 1 43 0 0
#> 108 18.29 1 39 0 1
#> 10.3 10.53 1 34 0 0
#> 81 14.06 1 34 0 0
#> 190.1 20.81 1 42 1 0
#> 101 9.97 1 10 0 1
#> 43.1 12.10 1 61 0 1
#> 5 16.43 1 51 0 1
#> 199.1 19.81 1 NA 0 1
#> 166 19.98 1 48 0 0
#> 175.1 21.91 1 43 0 0
#> 29.1 15.45 1 68 1 0
#> 130.2 16.47 1 53 0 1
#> 100.1 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 188.1 16.16 1 46 0 1
#> 190.2 20.81 1 42 1 0
#> 108.1 18.29 1 39 0 1
#> 158 20.14 1 74 1 0
#> 170 19.54 1 43 0 1
#> 101.1 9.97 1 10 0 1
#> 15.1 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 91 5.33 1 61 0 1
#> 86 23.81 1 58 0 1
#> 25 6.32 1 34 1 0
#> 154 12.63 1 20 1 0
#> 195.1 11.76 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 59 10.16 1 NA 1 0
#> 195.2 11.76 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 40.1 18.00 1 28 1 0
#> 175.2 21.91 1 43 0 0
#> 96 14.54 1 33 0 1
#> 5.1 16.43 1 51 0 1
#> 78.2 23.88 1 43 0 0
#> 154.1 12.63 1 20 1 0
#> 15.2 22.68 1 48 0 0
#> 142 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 9 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 44 24.00 0 56 0 0
#> 9.1 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 17 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 135 24.00 0 58 1 0
#> 3 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 141.1 24.00 0 44 1 0
#> 132 24.00 0 55 0 0
#> 173 24.00 0 19 0 1
#> 3.1 24.00 0 31 1 0
#> 33 24.00 0 53 0 0
#> 112 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 176 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 1 24.00 0 23 1 0
#> 31 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 11 24.00 0 42 0 1
#> 120 24.00 0 68 0 1
#> 172.1 24.00 0 41 0 0
#> 87.1 24.00 0 27 0 0
#> 138 24.00 0 44 1 0
#> 33.1 24.00 0 53 0 0
#> 44.1 24.00 0 56 0 0
#> 34 24.00 0 36 0 0
#> 116 24.00 0 58 0 1
#> 62 24.00 0 71 0 0
#> 143 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 185 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 33.2 24.00 0 53 0 0
#> 19 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 143.1 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 112.2 24.00 0 61 0 0
#> 178 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 196 24.00 0 19 0 0
#> 137 24.00 0 45 1 0
#> 83 24.00 0 6 0 0
#> 162 24.00 0 51 0 0
#> 131 24.00 0 66 0 0
#> 19.1 24.00 0 57 0 1
#> 72 24.00 0 40 0 1
#> 84.1 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 31.1 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 31.2 24.00 0 36 0 1
#> 132.1 24.00 0 55 0 0
#> 162.1 24.00 0 51 0 0
#> 87.2 24.00 0 27 0 0
#> 9.2 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 28 24.00 0 67 1 0
#> 144 24.00 0 28 0 1
#> 186 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 178.1 24.00 0 52 1 0
#> 87.3 24.00 0 27 0 0
#> 132.2 24.00 0 55 0 0
#> 104.1 24.00 0 50 1 0
#> 73.1 24.00 0 NA 0 1
#> 119 24.00 0 17 0 0
#> 2 24.00 0 9 0 0
#> 3.2 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 3.3 24.00 0 31 1 0
#> 17.1 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 132.3 24.00 0 55 0 0
#> 191.1 24.00 0 60 0 1
#> 31.3 24.00 0 36 0 1
#> 17.2 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.270 NA NA NA
#> 2 age, Cure model 0.0103 NA NA NA
#> 3 grade_ii, Cure model -0.213 NA NA NA
#> 4 grade_iii, Cure model 0.200 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00527 NA NA NA
#> 2 grade_ii, Survival model 0.876 NA NA NA
#> 3 grade_iii, Survival model 0.332 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.26961 0.01028 -0.21251 0.20040
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 258.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.26961012 0.01028464 -0.21250650 0.20039579
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005268463 0.876183500 0.331560764
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.359011941 0.603925604 0.092355681 0.114625837 0.908622574 0.318112748
#> [7] 0.055199784 0.874923832 0.410316963 0.114625837 0.440156198 0.659702498
#> [13] 0.603925604 0.258112045 0.191521209 0.823338785 0.067617580 0.732754830
#> [19] 0.687341934 0.659702498 0.908622574 0.891901630 0.159027096 0.891901630
#> [25] 0.641029859 0.857882178 0.213491604 0.778579323 0.622503505 0.546936834
#> [31] 0.147915641 0.488776274 0.017123837 0.975408236 0.796467967 0.287643258
#> [37] 0.659702498 0.796467967 0.440156198 0.488776274 0.696582459 0.246600886
#> [43] 0.814408206 0.967090876 0.348764817 0.080195252 0.114625837 0.488776274
#> [49] 0.338520975 0.908622574 0.741900017 0.546936834 0.866391649 0.823338785
#> [55] 0.369317470 0.191521209 0.005047143 0.092355681 0.440156198 0.369317470
#> [61] 0.517894967 0.778579323 0.714618435 0.741900017 0.714618435 0.941956220
#> [67] 0.527841244 0.440156198 0.017123837 0.389889497 0.908622574 0.769377629
#> [73] 0.258112045 0.950391028 0.874923832 0.584874837 0.307979357 0.213491604
#> [79] 0.696582459 0.546936834 0.641029859 0.478841724 0.622503505 0.258112045
#> [85] 0.389889497 0.297919945 0.328334405 0.950391028 0.159027096 0.575250115
#> [91] 0.991826219 0.043594414 0.983651749 0.840816486 0.420687324 0.527841244
#> [97] 0.420687324 0.213491604 0.760193949 0.584874837 0.017123837 0.840816486
#> [103] 0.159027096 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 179 79 92 113 10 105 168 43 51 113.1 184 39 79.1
#> 18.63 16.23 22.92 22.86 10.53 19.75 23.72 12.10 18.23 22.86 17.77 15.59 16.23
#> 190 194 140 164 180 167 39.1 10.1 107 15 107.1 100 37
#> 20.81 22.40 12.68 23.60 14.82 15.55 15.59 10.53 11.18 22.68 11.18 16.07 12.52
#> 175 60 188 130 63 45 78 70 155 68 39.2 155.1 184.1
#> 21.91 13.15 16.16 16.47 22.77 17.42 23.88 7.38 13.08 20.62 15.59 13.08 17.77
#> 45.1 29 136 123 187 97 69 113.2 45.2 58 10.2 133 130.1
#> 17.42 15.45 21.83 13.00 9.92 19.14 23.23 22.86 17.42 19.34 10.53 14.65 16.47
#> 56 140.1 88 194.1 24 92.1 184.2 88.1 23 60.1 157 133.1 157.1
#> 12.21 12.68 18.37 22.40 23.89 22.92 17.77 18.37 16.92 13.15 15.10 14.65 15.10
#> 61 106 184.3 78.1 108 10.3 81 190.1 101 43.1 5 166 175.1
#> 10.12 16.67 17.77 23.88 18.29 10.53 14.06 20.81 9.97 12.10 16.43 19.98 21.91
#> 29.1 130.2 100.1 117 188.1 190.2 108.1 158 170 101.1 15.1 85 91
#> 15.45 16.47 16.07 17.46 16.16 20.81 18.29 20.14 19.54 9.97 22.68 16.44 5.33
#> 86 25 154 40 106.1 40.1 175.2 96 5.1 78.2 154.1 15.2 142
#> 23.81 6.32 12.63 18.00 16.67 18.00 21.91 14.54 16.43 23.88 12.63 22.68 24.00
#> 20 9 87 44 9.1 94 17 104 135 3 141 141.1 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173 3.1 33 112 82 64 172 176 1 31 84 11 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.1 87.1 138 33.1 44.1 34 116 62 143 75 185 112.1 33.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 160 75.1 143.1 191 112.2 178 53 196 137 83 162 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19.1 72 84.1 102 31.1 156 20.1 31.2 132.1 162.1 87.2 9.2 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 144 186 174 126 178.1 87.3 132.2 104.1 119 2 3.2 182
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.3 17.1 193 132.3 191.1 31.3 17.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[32]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00113723 0.56483383 0.15971742
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.09783341 0.01963181 0.09102399
#> grade_iii, Cure model
#> 1.05611574
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 76 19.22 1 54 0 1
#> 10 10.53 1 34 0 0
#> 68 20.62 1 44 0 0
#> 111 17.45 1 47 0 1
#> 85 16.44 1 36 0 0
#> 113 22.86 1 34 0 0
#> 86 23.81 1 58 0 1
#> 164 23.60 1 76 0 1
#> 108 18.29 1 39 0 1
#> 49 12.19 1 48 1 0
#> 99 21.19 1 38 0 1
#> 29 15.45 1 68 1 0
#> 150 20.33 1 48 0 0
#> 18 15.21 1 49 1 0
#> 81 14.06 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 42 12.43 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 108.1 18.29 1 39 0 1
#> 45 17.42 1 54 0 1
#> 159 10.55 1 50 0 1
#> 23 16.92 1 61 0 0
#> 81.1 14.06 1 34 0 0
#> 170 19.54 1 43 0 1
#> 4 17.64 1 NA 0 1
#> 167 15.55 1 56 1 0
#> 77 7.27 1 67 0 1
#> 189 10.51 1 NA 1 0
#> 18.1 15.21 1 49 1 0
#> 49.2 12.19 1 48 1 0
#> 96 14.54 1 33 0 1
#> 188 16.16 1 46 0 1
#> 166 19.98 1 48 0 0
#> 96.1 14.54 1 33 0 1
#> 63 22.77 1 31 1 0
#> 155 13.08 1 26 0 0
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 55 19.34 1 69 0 1
#> 166.1 19.98 1 48 0 0
#> 157 15.10 1 47 0 0
#> 190 20.81 1 42 1 0
#> 92 22.92 1 47 0 1
#> 66 22.13 1 53 0 0
#> 129 23.41 1 53 1 0
#> 37 12.52 1 57 1 0
#> 88 18.37 1 47 0 0
#> 26 15.77 1 49 0 1
#> 179 18.63 1 42 0 0
#> 43 12.10 1 61 0 1
#> 79 16.23 1 54 1 0
#> 15 22.68 1 48 0 0
#> 69 23.23 1 25 0 1
#> 192 16.44 1 31 1 0
#> 166.2 19.98 1 48 0 0
#> 37.1 12.52 1 57 1 0
#> 79.1 16.23 1 54 1 0
#> 140 12.68 1 59 1 0
#> 117 17.46 1 26 0 1
#> 15.1 22.68 1 48 0 0
#> 5.1 16.43 1 51 0 1
#> 154 12.63 1 20 1 0
#> 68.2 20.62 1 44 0 0
#> 76.1 19.22 1 54 0 1
#> 77.1 7.27 1 67 0 1
#> 100 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 164.1 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 89 11.44 1 NA 0 0
#> 88.1 18.37 1 47 0 0
#> 90 20.94 1 50 0 1
#> 128 20.35 1 35 0 1
#> 100.1 16.07 1 60 0 0
#> 189.1 10.51 1 NA 1 0
#> 43.1 12.10 1 61 0 1
#> 145 10.07 1 65 1 0
#> 13 14.34 1 54 0 1
#> 125 15.65 1 67 1 0
#> 55.1 19.34 1 69 0 1
#> 166.3 19.98 1 48 0 0
#> 36 21.19 1 48 0 1
#> 77.2 7.27 1 67 0 1
#> 128.1 20.35 1 35 0 1
#> 181.1 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 139 21.49 1 63 1 0
#> 60 13.15 1 38 1 0
#> 169 22.41 1 46 0 0
#> 181.2 16.46 1 45 0 1
#> 29.1 15.45 1 68 1 0
#> 52.1 10.42 1 52 0 1
#> 113.1 22.86 1 34 0 0
#> 43.2 12.10 1 61 0 1
#> 66.1 22.13 1 53 0 0
#> 99.1 21.19 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 79.2 16.23 1 54 1 0
#> 123.1 13.00 1 44 1 0
#> 79.3 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 194 22.40 1 38 0 1
#> 36.1 21.19 1 48 0 1
#> 130 16.47 1 53 0 1
#> 129.1 23.41 1 53 1 0
#> 175.1 21.91 1 43 0 0
#> 110 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 6 15.64 1 39 0 0
#> 57 14.46 1 45 0 1
#> 108.2 18.29 1 39 0 1
#> 51 18.23 1 83 0 1
#> 120 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 174 24.00 0 49 1 0
#> 104 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 173 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 19 24.00 0 57 0 1
#> 163 24.00 0 66 0 0
#> 138 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 174.1 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 135 24.00 0 58 1 0
#> 80 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 132 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 126 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 80.1 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 72 24.00 0 40 0 1
#> 38.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 62 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 165.1 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 27 24.00 0 63 1 0
#> 156 24.00 0 50 1 0
#> 87.1 24.00 0 27 0 0
#> 31 24.00 0 36 0 1
#> 98 24.00 0 34 1 0
#> 115 24.00 0 NA 1 0
#> 67.1 24.00 0 25 0 0
#> 178 24.00 0 52 1 0
#> 47 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 200 24.00 0 64 0 0
#> 146 24.00 0 63 1 0
#> 38.2 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 71 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 19.1 24.00 0 57 0 1
#> 71.1 24.00 0 51 0 0
#> 186.1 24.00 0 45 1 0
#> 67.2 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#> 84 24.00 0 39 0 1
#> 144 24.00 0 28 0 1
#> 144.1 24.00 0 28 0 1
#> 160 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 161 24.00 0 45 0 0
#> 82.1 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 141.1 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 176.1 24.00 0 43 0 1
#> 120.1 24.00 0 68 0 1
#> 163.1 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 174.2 24.00 0 49 1 0
#> 196 24.00 0 19 0 0
#> 47.1 24.00 0 38 0 1
#> 103 24.00 0 56 1 0
#> 94 24.00 0 51 0 1
#> 120.2 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 83 24.00 0 6 0 0
#> 21 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 33.1 24.00 0 53 0 0
#> 73 24.00 0 NA 0 1
#> 138.1 24.00 0 44 1 0
#> 182.1 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.10 NA NA NA
#> 2 age, Cure model 0.0196 NA NA NA
#> 3 grade_ii, Cure model 0.0910 NA NA NA
#> 4 grade_iii, Cure model 1.06 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00114 NA NA NA
#> 2 grade_ii, Survival model 0.565 NA NA NA
#> 3 grade_iii, Survival model 0.160 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09783 0.01963 0.09102 1.05612
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 265.3
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.09783341 0.01963181 0.09102399 1.05611574
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00113723 0.56483383 0.15971742
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.41772257 0.94586809 0.29574221 0.53003615 0.59469282 0.10394870
#> [7] 0.01306689 0.03247870 0.47419919 0.89150791 0.23874893 0.72654949
#> [13] 0.34271226 0.74348269 0.80190423 0.29574221 0.88353107 0.89150791
#> [19] 0.47419919 0.53937570 0.93806074 0.54869858 0.80190423 0.38930565
#> [25] 0.71790567 0.97696295 0.74348269 0.89150791 0.76855533 0.66547021
#> [31] 0.35229644 0.76855533 0.12522684 0.82682093 0.61287964 0.56734931
#> [37] 0.39887971 0.35229644 0.76016373 0.28610995 0.09280110 0.17705937
#> [43] 0.06009329 0.86763374 0.45541232 0.69171003 0.44594057 0.91481231
#> [49] 0.63100889 0.13571102 0.08150318 0.59469282 0.35229644 0.86763374
#> [55] 0.63100889 0.85141485 0.52067811 0.13571102 0.61287964 0.85955182
#> [61] 0.29574221 0.41772257 0.97696295 0.67424494 0.95367788 0.03247870
#> [67] 0.83511870 0.45541232 0.27625306 0.32383960 0.67424494 0.91481231
#> [73] 0.96920672 0.79355663 0.70048619 0.39887971 0.35229644 0.23874893
#> [79] 0.97696295 0.32383960 0.56734931 0.19752245 0.22856771 0.81852559
#> [85] 0.15603515 0.56734931 0.72654949 0.95367788 0.10394870 0.91481231
#> [91] 0.17705937 0.23874893 0.63100889 0.83511870 0.63100889 0.43647819
#> [97] 0.16658811 0.23874893 0.55803209 0.06009329 0.19752245 0.51129664
#> [103] 0.21808904 0.70919361 0.78519995 0.47419919 0.50189973 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 76 10 68 111 85 113 86 164 108 49 99 29 150
#> 19.22 10.53 20.62 17.45 16.44 22.86 23.81 23.60 18.29 12.19 21.19 15.45 20.33
#> 18 81 68.1 42 49.1 108.1 45 159 23 81.1 170 167 77
#> 15.21 14.06 20.62 12.43 12.19 18.29 17.42 10.55 16.92 14.06 19.54 15.55 7.27
#> 18.1 49.2 96 188 166 96.1 63 155 5 181 55 166.1 157
#> 15.21 12.19 14.54 16.16 19.98 14.54 22.77 13.08 16.43 16.46 19.34 19.98 15.10
#> 190 92 66 129 37 88 26 179 43 79 15 69 192
#> 20.81 22.92 22.13 23.41 12.52 18.37 15.77 18.63 12.10 16.23 22.68 23.23 16.44
#> 166.2 37.1 79.1 140 117 15.1 5.1 154 68.2 76.1 77.1 100 52
#> 19.98 12.52 16.23 12.68 17.46 22.68 16.43 12.63 20.62 19.22 7.27 16.07 10.42
#> 164.1 123 88.1 90 128 100.1 43.1 145 13 125 55.1 166.3 36
#> 23.60 13.00 18.37 20.94 20.35 16.07 12.10 10.07 14.34 15.65 19.34 19.98 21.19
#> 77.2 128.1 181.1 175 139 60 169 181.2 29.1 52.1 113.1 43.2 66.1
#> 7.27 20.35 16.46 21.91 21.49 13.15 22.41 16.46 15.45 10.42 22.86 12.10 22.13
#> 99.1 79.2 123.1 79.3 97 194 36.1 130 129.1 175.1 110 136 6
#> 21.19 16.23 13.00 16.23 19.14 22.40 21.19 16.47 23.41 21.91 17.56 21.83 15.64
#> 57 108.2 51 120 141 11 174 104 165 38 173 176 19
#> 14.46 18.29 18.23 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 138 151 174.1 172 135 80 191 132 137 67 126 122
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 82 72 38.1 87 62 109 95 131 75 165.1 186 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 87.1 31 98 67.1 178 47 9 46 200 146 38.2 132.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 121 19.1 71.1 186.1 67.2 200.1 84 144 144.1 160 118 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 82.1 143 182 141.1 22 176.1 120.1 163.1 33 72.1 174.2 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 103 94 120.2 103.1 83 21 34 33.1 138.1 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[33]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02216879 0.45496159 0.09606925
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.209701949 -0.007622566 0.454939743
#> grade_iii, Cure model
#> 0.709489275
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 45 17.42 1 54 0 1
#> 13 14.34 1 54 0 1
#> 43 12.10 1 61 0 1
#> 25 6.32 1 34 1 0
#> 184 17.77 1 38 0 0
#> 129 23.41 1 53 1 0
#> 68 20.62 1 44 0 0
#> 14 12.89 1 21 0 0
#> 187 9.92 1 39 1 0
#> 108 18.29 1 39 0 1
#> 170 19.54 1 43 0 1
#> 192 16.44 1 31 1 0
#> 61 10.12 1 36 0 1
#> 125 15.65 1 67 1 0
#> 140 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 117 17.46 1 26 0 1
#> 23 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 15 22.68 1 48 0 0
#> 129.1 23.41 1 53 1 0
#> 127 3.53 1 62 0 1
#> 70 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 26 15.77 1 49 0 1
#> 91 5.33 1 61 0 1
#> 6 15.64 1 39 0 0
#> 177 12.53 1 75 0 0
#> 139 21.49 1 63 1 0
#> 184.1 17.77 1 38 0 0
#> 117.1 17.46 1 26 0 1
#> 149 8.37 1 33 1 0
#> 32 20.90 1 37 1 0
#> 117.2 17.46 1 26 0 1
#> 113 22.86 1 34 0 0
#> 6.1 15.64 1 39 0 0
#> 192.1 16.44 1 31 1 0
#> 197 21.60 1 69 1 0
#> 49 12.19 1 48 1 0
#> 149.1 8.37 1 33 1 0
#> 190 20.81 1 42 1 0
#> 37 12.52 1 57 1 0
#> 169 22.41 1 46 0 0
#> 181 16.46 1 45 0 1
#> 15.1 22.68 1 48 0 0
#> 45.1 17.42 1 54 0 1
#> 155 13.08 1 26 0 0
#> 45.2 17.42 1 54 0 1
#> 66 22.13 1 53 0 0
#> 81.1 14.06 1 34 0 0
#> 155.1 13.08 1 26 0 0
#> 127.1 3.53 1 62 0 1
#> 180 14.82 1 37 0 0
#> 39 15.59 1 37 0 1
#> 133 14.65 1 57 0 0
#> 76 19.22 1 54 0 1
#> 70.1 7.38 1 30 1 0
#> 96 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 88 18.37 1 47 0 0
#> 128 20.35 1 35 0 1
#> 171 16.57 1 41 0 1
#> 85 16.44 1 36 0 0
#> 171.1 16.57 1 41 0 1
#> 192.2 16.44 1 31 1 0
#> 79 16.23 1 54 1 0
#> 192.3 16.44 1 31 1 0
#> 117.3 17.46 1 26 0 1
#> 88.1 18.37 1 47 0 0
#> 125.1 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 136 21.83 1 43 0 1
#> 97 19.14 1 65 0 1
#> 124 9.73 1 NA 1 0
#> 70.2 7.38 1 30 1 0
#> 15.2 22.68 1 48 0 0
#> 56 12.21 1 60 0 0
#> 110 17.56 1 65 0 1
#> 153 21.33 1 55 1 0
#> 171.2 16.57 1 41 0 1
#> 91.1 5.33 1 61 0 1
#> 154 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 37.1 12.52 1 57 1 0
#> 139.1 21.49 1 63 1 0
#> 125.2 15.65 1 67 1 0
#> 180.1 14.82 1 37 0 0
#> 45.3 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 29 15.45 1 68 1 0
#> 168 23.72 1 70 0 0
#> 114 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 179 18.63 1 42 0 0
#> 158.1 20.14 1 74 1 0
#> 36.1 21.19 1 48 0 1
#> 92 22.92 1 47 0 1
#> 93 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 15.3 22.68 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 60.1 13.15 1 38 1 0
#> 41 18.02 1 40 1 0
#> 179.1 18.63 1 42 0 0
#> 5 16.43 1 51 0 1
#> 14.1 12.89 1 21 0 0
#> 92.1 22.92 1 47 0 1
#> 4 17.64 1 NA 0 1
#> 140.1 12.68 1 59 1 0
#> 125.3 15.65 1 67 1 0
#> 32.1 20.90 1 37 1 0
#> 173 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 160 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 174 24.00 0 49 1 0
#> 122 24.00 0 66 0 0
#> 11 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 122.1 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 151 24.00 0 42 0 0
#> 103 24.00 0 56 1 0
#> 146 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 126.1 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 33.1 24.00 0 53 0 0
#> 34 24.00 0 36 0 0
#> 131 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 144.1 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 62 24.00 0 71 0 0
#> 162 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 9 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 121 24.00 0 57 1 0
#> 156.1 24.00 0 50 1 0
#> 104 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 71 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 162.1 24.00 0 51 0 0
#> 11.1 24.00 0 42 0 1
#> 33.2 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 82 24.00 0 34 0 0
#> 147.1 24.00 0 76 1 0
#> 176.1 24.00 0 43 0 1
#> 22 24.00 0 52 1 0
#> 109.1 24.00 0 48 0 0
#> 38 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 196 24.00 0 19 0 0
#> 162.2 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 147.2 24.00 0 76 1 0
#> 163 24.00 0 66 0 0
#> 9.1 24.00 0 31 1 0
#> 11.2 24.00 0 42 0 1
#> 104.1 24.00 0 50 1 0
#> 71.1 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 62.1 24.00 0 71 0 0
#> 9.2 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 173.1 24.00 0 19 0 1
#> 11.3 24.00 0 42 0 1
#> 95 24.00 0 68 0 1
#> 21.1 24.00 0 47 0 0
#> 83 24.00 0 6 0 0
#> 20.1 24.00 0 46 1 0
#> 19 24.00 0 57 0 1
#> 19.1 24.00 0 57 0 1
#> 104.2 24.00 0 50 1 0
#> 200 24.00 0 64 0 0
#> 160.1 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 35 24.00 0 51 0 0
#> 104.3 24.00 0 50 1 0
#> 95.1 24.00 0 68 0 1
#> 80 24.00 0 41 0 0
#> 148.1 24.00 0 61 1 0
#> 7 24.00 0 37 1 0
#> 9.3 24.00 0 31 1 0
#> 122.2 24.00 0 66 0 0
#> 84 24.00 0 39 0 1
#> 162.3 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.210 NA NA NA
#> 2 age, Cure model -0.00762 NA NA NA
#> 3 grade_ii, Cure model 0.455 NA NA NA
#> 4 grade_iii, Cure model 0.709 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0222 NA NA NA
#> 2 grade_ii, Survival model 0.455 NA NA NA
#> 3 grade_iii, Survival model 0.0961 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.209702 -0.007623 0.454940 0.709489
#>
#> Degrees of Freedom: 195 Total (i.e. Null); 192 Residual
#> Null Deviance: 269.2
#> Residual Deviance: 264.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.209701949 -0.007622566 0.454939743 0.709489275
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02216879 0.45496159 0.09606925
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 1.313221e-01 4.524575e-01 7.256457e-01 9.046174e-01 8.807092e-02
#> [6] 1.266990e-04 3.135779e-02 5.516619e-01 7.960754e-01 7.695844e-02
#> [11] 4.498636e-02 2.113011e-01 7.781264e-01 2.963413e-01 5.813722e-01
#> [16] 4.661885e-01 1.061011e-01 1.602592e-01 4.941040e-01 1.689534e-03
#> [21] 1.266990e-04 9.610417e-01 8.503160e-01 6.827009e-07 2.858666e-01
#> [26] 9.231905e-01 3.398232e-01 6.274761e-01 1.162536e-02 8.807092e-02
#> [31] 1.061011e-01 8.141615e-01 2.295535e-02 1.061011e-01 1.172440e-03
#> [36] 3.398232e-01 2.113011e-01 9.847867e-03 7.086729e-01 8.141615e-01
#> [41] 2.838527e-02 6.432884e-01 4.463813e-03 1.933200e-01 1.689534e-03
#> [46] 1.313221e-01 5.225357e-01 1.313221e-01 6.829621e-03 4.661885e-01
#> [51] 5.225357e-01 9.610417e-01 4.001738e-01 3.632036e-01 4.257321e-01
#> [56] 4.890942e-02 8.503160e-01 4.389992e-01 7.429072e-01 6.674552e-02
#> [61] 3.451696e-02 1.683330e-01 2.113011e-01 1.683330e-01 2.113011e-01
#> [66] 2.657554e-01 2.113011e-01 1.061011e-01 6.674552e-02 2.963413e-01
#> [71] 3.876395e-01 8.259437e-03 5.305446e-02 8.503160e-01 1.689534e-03
#> [76] 6.918836e-01 9.978071e-02 1.559620e-02 1.683330e-01 9.231905e-01
#> [81] 6.119803e-01 1.933200e-01 6.432884e-01 1.162536e-02 2.963413e-01
#> [86] 4.001738e-01 1.313221e-01 1.789532e-02 3.752921e-01 1.825547e-05
#> [91] 3.782562e-02 5.580770e-03 5.745370e-02 3.782562e-02 1.789532e-02
#> [96] 4.851102e-04 7.603838e-01 6.753887e-01 1.689534e-03 2.657554e-01
#> [101] 4.941040e-01 8.244899e-02 5.745370e-02 2.559007e-01 5.516619e-01
#> [106] 4.851102e-04 5.813722e-01 2.963413e-01 2.295535e-02 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [196] 0.000000e+00
#>
#> $Time
#> 45 13 43 25 184 129 68 14 187 108 170 192 61
#> 17.42 14.34 12.10 6.32 17.77 23.41 20.62 12.89 9.92 18.29 19.54 16.44 10.12
#> 125 140 81 117 23 60 15 129.1 127 70 86 26 91
#> 15.65 12.68 14.06 17.46 16.92 13.15 22.68 23.41 3.53 7.38 23.81 15.77 5.33
#> 6 177 139 184.1 117.1 149 32 117.2 113 6.1 192.1 197 49
#> 15.64 12.53 21.49 17.77 17.46 8.37 20.90 17.46 22.86 15.64 16.44 21.60 12.19
#> 149.1 190 37 169 181 15.1 45.1 155 45.2 66 81.1 155.1 127.1
#> 8.37 20.81 12.52 22.41 16.46 22.68 17.42 13.08 17.42 22.13 14.06 13.08 3.53
#> 180 39 133 76 70.1 96 10 88 128 171 85 171.1 192.2
#> 14.82 15.59 14.65 19.22 7.38 14.54 10.53 18.37 20.35 16.57 16.44 16.57 16.44
#> 79 192.3 117.3 88.1 125.1 18 136 97 70.2 15.2 56 110 153
#> 16.23 16.44 17.46 18.37 15.65 15.21 21.83 19.14 7.38 22.68 12.21 17.56 21.33
#> 171.2 91.1 154 181.1 37.1 139.1 125.2 180.1 45.3 36 29 168 158
#> 16.57 5.33 12.63 16.46 12.52 21.49 15.65 14.82 17.42 21.19 15.45 23.72 20.14
#> 194 179 158.1 36.1 92 93 42 15.3 79.1 60.1 41 179.1 5
#> 22.40 18.63 20.14 21.19 22.92 10.33 12.43 22.68 16.23 13.15 18.02 18.63 16.43
#> 14.1 92.1 140.1 125.3 32.1 173 126 72 160 156 174 122 11
#> 12.89 22.92 12.68 15.65 20.90 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 122.1 21 144 17 33 148 151 103 146 141 126.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 34 131 191 144.1 46 62 162 72.1 9 20 121 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 47 176 64 71 147 162.1 11.1 33.2 109 82 147.1 176.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 109.1 38 64.1 196 162.2 135 147.2 163 9.1 11.2 104.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 62.1 9.2 173.1 11.3 95 21.1 83 20.1 19 19.1 104.2 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 47.1 44 35 104.3 95.1 80 148.1 7 9.3 122.2 84 162.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[34]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01098758 0.81188522 0.34440196
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74324006 0.01234911 0.12514018
#> grade_iii, Cure model
#> 0.67971149
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 110 17.56 1 65 0 1
#> 14 12.89 1 21 0 0
#> 58 19.34 1 39 0 0
#> 190 20.81 1 42 1 0
#> 89 11.44 1 NA 0 0
#> 101 9.97 1 10 0 1
#> 57 14.46 1 45 0 1
#> 56 12.21 1 60 0 0
#> 158 20.14 1 74 1 0
#> 124 9.73 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 42 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 78 23.88 1 43 0 0
#> 10 10.53 1 34 0 0
#> 124.1 9.73 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 149 8.37 1 33 1 0
#> 61 10.12 1 36 0 1
#> 78.1 23.88 1 43 0 0
#> 8 18.43 1 32 0 0
#> 89.1 11.44 1 NA 0 0
#> 61.1 10.12 1 36 0 1
#> 125 15.65 1 67 1 0
#> 18 15.21 1 49 1 0
#> 57.1 14.46 1 45 0 1
#> 5 16.43 1 51 0 1
#> 164 23.60 1 76 0 1
#> 149.1 8.37 1 33 1 0
#> 158.1 20.14 1 74 1 0
#> 188 16.16 1 46 0 1
#> 86 23.81 1 58 0 1
#> 124.2 9.73 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 181 16.46 1 45 0 1
#> 78.2 23.88 1 43 0 0
#> 88.1 18.37 1 47 0 0
#> 40 18.00 1 28 1 0
#> 106.1 16.67 1 49 1 0
#> 50 10.02 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 125.1 15.65 1 67 1 0
#> 6 15.64 1 39 0 0
#> 49 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 69 23.23 1 25 0 1
#> 8.1 18.43 1 32 0 0
#> 181.1 16.46 1 45 0 1
#> 108 18.29 1 39 0 1
#> 107.1 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 29 15.45 1 68 1 0
#> 188.1 16.16 1 46 0 1
#> 37 12.52 1 57 1 0
#> 91 5.33 1 61 0 1
#> 88.2 18.37 1 47 0 0
#> 42.2 12.43 1 49 0 1
#> 14.1 12.89 1 21 0 0
#> 89.2 11.44 1 NA 0 0
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 96 14.54 1 33 0 1
#> 40.1 18.00 1 28 1 0
#> 181.2 16.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 175 21.91 1 43 0 0
#> 97 19.14 1 65 0 1
#> 124.3 9.73 1 NA 1 0
#> 89.3 11.44 1 NA 0 0
#> 164.1 23.60 1 76 0 1
#> 15 22.68 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 43 12.10 1 61 0 1
#> 69.1 23.23 1 25 0 1
#> 194 22.40 1 38 0 1
#> 145 10.07 1 65 1 0
#> 4 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 179 18.63 1 42 0 0
#> 88.3 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 164.2 23.60 1 76 0 1
#> 30 17.43 1 78 0 0
#> 139.1 21.49 1 63 1 0
#> 10.1 10.53 1 34 0 0
#> 8.2 18.43 1 32 0 0
#> 45 17.42 1 54 0 1
#> 114 13.68 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 153 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 130 16.47 1 53 0 1
#> 69.2 23.23 1 25 0 1
#> 6.2 15.64 1 39 0 0
#> 124.4 9.73 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 169.1 22.41 1 46 0 0
#> 36 21.19 1 48 0 1
#> 76 19.22 1 54 0 1
#> 76.1 19.22 1 54 0 1
#> 37.1 12.52 1 57 1 0
#> 93 10.33 1 52 0 1
#> 179.2 18.63 1 42 0 0
#> 92 22.92 1 47 0 1
#> 171 16.57 1 41 0 1
#> 149.2 8.37 1 33 1 0
#> 37.2 12.52 1 57 1 0
#> 124.5 9.73 1 NA 1 0
#> 182 24.00 0 35 0 0
#> 152 24.00 0 36 0 1
#> 53 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 121 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 54 24.00 0 53 1 0
#> 34 24.00 0 36 0 0
#> 146 24.00 0 63 1 0
#> 122 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 82 24.00 0 34 0 0
#> 152.1 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 20 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 44 24.00 0 56 0 0
#> 156 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 198 24.00 0 66 0 1
#> 48 24.00 0 31 1 0
#> 33.2 24.00 0 53 0 0
#> 28 24.00 0 67 1 0
#> 138 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 178 24.00 0 52 1 0
#> 160 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 20.1 24.00 0 46 1 0
#> 53.1 24.00 0 32 0 1
#> 116 24.00 0 58 0 1
#> 83 24.00 0 6 0 0
#> 64 24.00 0 43 0 0
#> 46 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 120 24.00 0 68 0 1
#> 200 24.00 0 64 0 0
#> 34.1 24.00 0 36 0 0
#> 146.1 24.00 0 63 1 0
#> 28.1 24.00 0 67 1 0
#> 3.1 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 102 24.00 0 49 0 0
#> 193.1 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 147 24.00 0 76 1 0
#> 53.2 24.00 0 32 0 1
#> 200.1 24.00 0 64 0 0
#> 12 24.00 0 63 0 0
#> 17.1 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 104.1 24.00 0 50 1 0
#> 165 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 20.2 24.00 0 46 1 0
#> 119.1 24.00 0 17 0 0
#> 74 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 2.1 24.00 0 9 0 0
#> 120.1 24.00 0 68 0 1
#> 53.3 24.00 0 32 0 1
#> 178.1 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 160.1 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 83.1 24.00 0 6 0 0
#> 151 24.00 0 42 0 0
#> 162.1 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 53.4 24.00 0 32 0 1
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 172 24.00 0 41 0 0
#> 34.2 24.00 0 36 0 0
#> 152.2 24.00 0 36 0 1
#> 178.2 24.00 0 52 1 0
#> 193.2 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.743 NA NA NA
#> 2 age, Cure model 0.0123 NA NA NA
#> 3 grade_ii, Cure model 0.125 NA NA NA
#> 4 grade_iii, Cure model 0.680 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0110 NA NA NA
#> 2 grade_ii, Survival model 0.812 NA NA NA
#> 3 grade_iii, Survival model 0.344 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74324 0.01235 0.12514 0.67971
#>
#> Degrees of Freedom: 181 Total (i.e. Null); 178 Residual
#> Null Deviance: 252
#> Residual Deviance: 246.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74324006 0.01234911 0.12514018 0.67971149
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01098758 0.81188522 0.34440196
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.431823834 0.714228359 0.239740458 0.210484260 0.943319001 0.679869800
#> [7] 0.804829461 0.220383503 0.862308199 0.770836256 0.343088907 0.003505756
#> [13] 0.873822479 0.150690356 0.954917527 0.908525827 0.003505756 0.311108469
#> [19] 0.908525827 0.588738314 0.656882938 0.679869800 0.543451047 0.025547528
#> [25] 0.954917527 0.220383503 0.566169912 0.017432755 0.465588871 0.510131208
#> [31] 0.003505756 0.343088907 0.398805125 0.465588871 0.770836256 0.588738314
#> [37] 0.611238986 0.816403712 0.839489483 0.050109798 0.311108469 0.510131208
#> [43] 0.387234892 0.839489483 0.200385839 0.160932824 0.420786265 0.645327712
#> [49] 0.566169912 0.737105544 0.988604562 0.343088907 0.770836256 0.714228359
#> [55] 0.092901736 0.668374586 0.398805125 0.510131208 0.554838880 0.140409591
#> [61] 0.269763998 0.025547528 0.101912788 0.611238986 0.827924221 0.050109798
#> [67] 0.130404856 0.931682662 0.702772925 0.280075606 0.343088907 0.111263022
#> [73] 0.025547528 0.442949319 0.160932824 0.873822479 0.311108469 0.454238008
#> [79] 0.280075606 0.180463318 0.083333184 0.498878584 0.050109798 0.611238986
#> [85] 0.111263022 0.190380949 0.249766686 0.249766686 0.737105544 0.896887578
#> [91] 0.280075606 0.074096043 0.487679457 0.954917527 0.737105544 0.000000000
#> [97] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000
#>
#> $Time
#> 110 14 58 190 101 57 56 158 159 42 88 78 10
#> 17.56 12.89 19.34 20.81 9.97 14.46 12.21 20.14 10.55 12.43 18.37 23.88 10.53
#> 197 149 61 78.1 8 61.1 125 18 57.1 5 164 149.1 158.1
#> 21.60 8.37 10.12 23.88 18.43 10.12 15.65 15.21 14.46 16.43 23.60 8.37 20.14
#> 188 86 106 181 78.2 88.1 40 106.1 42.1 125.1 6 49 107
#> 16.16 23.81 16.67 16.46 23.88 18.37 18.00 16.67 12.43 15.65 15.64 12.19 11.18
#> 69 8.1 181.1 108 107.1 90 139 134 29 188.1 37 91 88.2
#> 23.23 18.43 16.46 18.29 11.18 20.94 21.49 17.81 15.45 16.16 12.52 5.33 18.37
#> 42.2 14.1 63 96 40.1 181.2 79 175 97 164.1 15 6.1 43
#> 12.43 12.89 22.77 14.54 18.00 16.46 16.23 21.91 19.14 23.60 22.68 15.64 12.10
#> 69.1 194 145 60 179 88.3 169 164.2 30 139.1 10.1 8.2 45
#> 23.23 22.40 10.07 13.15 18.63 18.37 22.41 23.60 17.43 21.49 10.53 18.43 17.42
#> 179.1 153 113 130 69.2 6.2 169.1 36 76 76.1 37.1 93 179.2
#> 18.63 21.33 22.86 16.47 23.23 15.64 22.41 21.19 19.22 19.22 12.52 10.33 18.63
#> 92 171 149.2 37.2 182 152 53 71 132 193 121 62 148
#> 22.92 16.57 8.37 12.52 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 34 146 122 33 82 152.1 3 33.1 20 173 44 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 198 48 33.2 28 138 119 178 160 104 20.1 53.1 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 64 46 7 17 112 120 200 34.1 146.1 28.1 3.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 193.1 2 147 53.2 200.1 12 17.1 98 104.1 165 118 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 119.1 74 80 186 2.1 120.1 53.3 178.1 71.1 11 160.1 11.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 151 162.1 95 53.4 103 38 67 172 34.2 152.2 178.2 193.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[35]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007542283 0.505840778 0.275441786
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.652251868 0.005142588 0.637485440
#> grade_iii, Cure model
#> 0.991689600
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 41.1 18.02 1 40 1 0
#> 77 7.27 1 67 0 1
#> 45 17.42 1 54 0 1
#> 37 12.52 1 57 1 0
#> 166 19.98 1 48 0 0
#> 97 19.14 1 65 0 1
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 25 6.32 1 34 1 0
#> 77.1 7.27 1 67 0 1
#> 154 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 32 20.90 1 37 1 0
#> 110 17.56 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 77.2 7.27 1 67 0 1
#> 88 18.37 1 47 0 0
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 25.1 6.32 1 34 1 0
#> 89.1 11.44 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 113 22.86 1 34 0 0
#> 179 18.63 1 42 0 0
#> 140 12.68 1 59 1 0
#> 167 15.55 1 56 1 0
#> 57 14.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 42 12.43 1 49 0 1
#> 145 10.07 1 65 1 0
#> 96 14.54 1 33 0 1
#> 154.1 12.63 1 20 1 0
#> 60 13.15 1 38 1 0
#> 18 15.21 1 49 1 0
#> 45.1 17.42 1 54 0 1
#> 111 17.45 1 47 0 1
#> 107 11.18 1 54 1 0
#> 197 21.60 1 69 1 0
#> 129 23.41 1 53 1 0
#> 15 22.68 1 48 0 0
#> 85 16.44 1 36 0 0
#> 130 16.47 1 53 0 1
#> 134 17.81 1 47 1 0
#> 52 10.42 1 52 0 1
#> 153 21.33 1 55 1 0
#> 114 13.68 1 NA 0 0
#> 128 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 157 15.10 1 47 0 0
#> 171 16.57 1 41 0 1
#> 129.1 23.41 1 53 1 0
#> 89.2 11.44 1 NA 0 0
#> 49 12.19 1 48 1 0
#> 60.1 13.15 1 38 1 0
#> 124 9.73 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 195 11.76 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 187 9.92 1 39 1 0
#> 90 20.94 1 50 0 1
#> 192 16.44 1 31 1 0
#> 197.1 21.60 1 69 1 0
#> 145.1 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 57.1 14.46 1 45 0 1
#> 195.1 11.76 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 183 9.24 1 67 1 0
#> 8.1 18.43 1 32 0 0
#> 153.1 21.33 1 55 1 0
#> 58 19.34 1 39 0 0
#> 68 20.62 1 44 0 0
#> 100 16.07 1 60 0 0
#> 153.2 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 30 17.43 1 78 0 0
#> 50.1 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 101.1 9.97 1 10 0 1
#> 32.1 20.90 1 37 1 0
#> 187.1 9.92 1 39 1 0
#> 107.1 11.18 1 54 1 0
#> 105.1 19.75 1 60 0 0
#> 187.2 9.92 1 39 1 0
#> 68.1 20.62 1 44 0 0
#> 164 23.60 1 76 0 1
#> 25.2 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 189 10.51 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 88.1 18.37 1 47 0 0
#> 140.1 12.68 1 59 1 0
#> 171.1 16.57 1 41 0 1
#> 13.1 14.34 1 54 0 1
#> 57.2 14.46 1 45 0 1
#> 49.1 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 123 13.00 1 44 1 0
#> 149 8.37 1 33 1 0
#> 49.2 12.19 1 48 1 0
#> 43.1 12.10 1 61 0 1
#> 15.1 22.68 1 48 0 0
#> 69.1 23.23 1 25 0 1
#> 158 20.14 1 74 1 0
#> 134.1 17.81 1 47 1 0
#> 136 21.83 1 43 0 1
#> 29.1 15.45 1 68 1 0
#> 167.1 15.55 1 56 1 0
#> 77.3 7.27 1 67 0 1
#> 147 24.00 0 76 1 0
#> 67 24.00 0 25 0 0
#> 176 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 3 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 186 24.00 0 45 1 0
#> 148 24.00 0 61 1 0
#> 3.2 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 198 24.00 0 66 0 1
#> 3.3 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 84 24.00 0 39 0 1
#> 47.1 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 173 24.00 0 19 0 1
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 82 24.00 0 34 0 0
#> 48 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 34 24.00 0 36 0 0
#> 98 24.00 0 34 1 0
#> 34.1 24.00 0 36 0 0
#> 47.2 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 186.1 24.00 0 45 1 0
#> 198.1 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 147.1 24.00 0 76 1 0
#> 115 24.00 0 NA 1 0
#> 137.1 24.00 0 45 1 0
#> 185 24.00 0 44 1 0
#> 147.2 24.00 0 76 1 0
#> 64 24.00 0 43 0 0
#> 94 24.00 0 51 0 1
#> 1 24.00 0 23 1 0
#> 163 24.00 0 66 0 0
#> 156 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 82.2 24.00 0 34 0 0
#> 151.1 24.00 0 42 0 0
#> 64.1 24.00 0 43 0 0
#> 74 24.00 0 43 0 1
#> 38 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 73 24.00 0 NA 0 1
#> 115.1 24.00 0 NA 1 0
#> 138.1 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 146.1 24.00 0 63 1 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 95 24.00 0 68 0 1
#> 38.1 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 148.1 24.00 0 61 1 0
#> 54 24.00 0 53 1 0
#> 71.1 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 9.2 24.00 0 31 1 0
#> 120.1 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 163.1 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 34.2 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 94.1 24.00 0 51 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.652 NA NA NA
#> 2 age, Cure model 0.00514 NA NA NA
#> 3 grade_ii, Cure model 0.637 NA NA NA
#> 4 grade_iii, Cure model 0.992 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00754 NA NA NA
#> 2 grade_ii, Survival model 0.506 NA NA NA
#> 3 grade_iii, Survival model 0.275 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.652252 0.005143 0.637485 0.991690
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.2
#> Residual Deviance: 248.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.652251868 0.005142588 0.637485440 0.991689600
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007542283 0.505840778 0.275441786
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.211414985 0.330147855 0.330147855 0.919468235 0.401208381 0.714514160
#> [7] 0.202000209 0.269457036 0.556986548 0.609451627 0.959745556 0.919468235
#> [13] 0.693838190 0.048521656 0.147871005 0.370410376 0.919468235 0.309638200
#> [19] 0.230428632 0.959745556 0.289526483 0.057208584 0.279442829 0.672896331
#> [25] 0.494452626 0.578164989 0.838131148 0.724916078 0.817527848 0.567578423
#> [31] 0.693838190 0.641278417 0.536002769 0.401208381 0.380622272 0.786575554
#> [37] 0.094100266 0.016764580 0.066206689 0.452833184 0.442380215 0.350373433
#> [43] 0.807156341 0.112566853 0.183456411 0.909322032 0.546464595 0.421777509
#> [49] 0.016764580 0.735331424 0.641278417 0.515224705 0.630582213 0.858622938
#> [55] 0.138545234 0.452833184 0.094100266 0.817527848 0.032900921 0.578164989
#> [61] 0.989845163 0.888922430 0.289526483 0.112566853 0.240159722 0.165392822
#> [67] 0.483916273 0.112566853 0.765938873 0.390855049 0.249992382 0.838131148
#> [73] 0.147871005 0.858622938 0.786575554 0.211414985 0.858622938 0.165392822
#> [79] 0.004359747 0.959745556 0.473462772 0.249992382 0.309638200 0.672896331
#> [85] 0.421777509 0.609451627 0.578164989 0.735331424 0.662321858 0.899139180
#> [91] 0.735331424 0.765938873 0.066206689 0.032900921 0.192716906 0.350373433
#> [97] 0.084398775 0.515224705 0.494452626 0.919468235 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 105 41 41.1 77 45 37 166 97 133 13 25 77.1 154
#> 19.75 18.02 18.02 7.27 17.42 12.52 19.98 19.14 14.65 14.34 6.32 7.27 12.63
#> 92 32 110 77.2 88 170 25.1 8 113 179 140 167 57
#> 22.92 20.90 17.56 7.27 18.37 19.54 6.32 18.43 22.86 18.63 12.68 15.55 14.46
#> 101 42 145 96 154.1 60 18 45.1 111 107 197 129 15
#> 9.97 12.43 10.07 14.54 12.63 13.15 15.21 17.42 17.45 11.18 21.60 23.41 22.68
#> 85 130 134 52 153 128 70 157 171 129.1 49 60.1 29
#> 16.44 16.47 17.81 10.42 21.33 20.35 7.38 15.10 16.57 23.41 12.19 13.15 15.45
#> 81 187 90 192 197.1 145.1 69 57.1 127 183 8.1 153.1 58
#> 14.06 9.92 20.94 16.44 21.60 10.07 23.23 14.46 3.53 9.24 18.43 21.33 19.34
#> 68 100 153.2 43 30 76 101.1 32.1 187.1 107.1 105.1 187.2 68.1
#> 20.62 16.07 21.33 12.10 17.43 19.22 9.97 20.90 9.92 11.18 19.75 9.92 20.62
#> 164 25.2 5 76.1 88.1 140.1 171.1 13.1 57.2 49.1 123 149 49.2
#> 23.60 6.32 16.43 19.22 18.37 12.68 16.57 14.34 14.46 12.19 13.00 8.37 12.19
#> 43.1 15.1 69.1 158 134.1 136 29.1 167.1 77.3 147 67 176 47
#> 12.10 22.68 23.23 20.14 17.81 21.83 15.45 15.55 7.27 24.00 24.00 24.00 24.00
#> 3 137 3.1 19 186 148 3.2 118 62 35 12 198 3.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 46 84 47.1 182 17 151 173 126 102 174 82 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 46.1 84.1 34 98 34.1 47.2 200 186.1 198.1 172 9 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 147.1 137.1 185 147.2 64 94 1 163 156 196 33 82.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 64.1 74 38 162 135 138.1 74.1 146 27 146.1 71 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 38.1 48.1 148.1 54 71.1 120 9.2 120.1 122 22 163.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 53 94.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[36]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01089215 0.65143986 0.13604953
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.361621614 -0.007912597 -0.115853291
#> grade_iii, Cure model
#> 0.761992223
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 187 9.92 1 39 1 0
#> 43 12.10 1 61 0 1
#> 99 21.19 1 38 0 1
#> 56 12.21 1 60 0 0
#> 91 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 187.1 9.92 1 39 1 0
#> 199 19.81 1 NA 0 1
#> 69 23.23 1 25 0 1
#> 157 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 76 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 78 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 41 18.02 1 40 1 0
#> 56.1 12.21 1 60 0 0
#> 66 22.13 1 53 0 0
#> 81 14.06 1 34 0 0
#> 25 6.32 1 34 1 0
#> 23 16.92 1 61 0 0
#> 155 13.08 1 26 0 0
#> 26 15.77 1 49 0 1
#> 149 8.37 1 33 1 0
#> 41.1 18.02 1 40 1 0
#> 140 12.68 1 59 1 0
#> 150 20.33 1 48 0 0
#> 32 20.90 1 37 1 0
#> 124 9.73 1 NA 1 0
#> 157.1 15.10 1 47 0 0
#> 175 21.91 1 43 0 0
#> 14 12.89 1 21 0 0
#> 195 11.76 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 192 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 101 9.97 1 10 0 1
#> 37.1 12.52 1 57 1 0
#> 199.1 19.81 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 26.1 15.77 1 49 0 1
#> 63 22.77 1 31 1 0
#> 60 13.15 1 38 1 0
#> 127 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 86 23.81 1 58 0 1
#> 101.1 9.97 1 10 0 1
#> 30 17.43 1 78 0 0
#> 150.1 20.33 1 48 0 0
#> 99.1 21.19 1 38 0 1
#> 169 22.41 1 46 0 0
#> 69.1 23.23 1 25 0 1
#> 57 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 124.1 9.73 1 NA 1 0
#> 177 12.53 1 75 0 0
#> 49 12.19 1 48 1 0
#> 4 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 91.1 5.33 1 61 0 1
#> 10.1 10.53 1 34 0 0
#> 88 18.37 1 47 0 0
#> 16 8.71 1 71 0 1
#> 192.1 16.44 1 31 1 0
#> 56.2 12.21 1 60 0 0
#> 175.1 21.91 1 43 0 0
#> 51 18.23 1 83 0 1
#> 60.1 13.15 1 38 1 0
#> 181 16.46 1 45 0 1
#> 50 10.02 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 199.2 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 180 14.82 1 37 0 0
#> 14.1 12.89 1 21 0 0
#> 61 10.12 1 36 0 1
#> 40.1 18.00 1 28 1 0
#> 77 7.27 1 67 0 1
#> 166 19.98 1 48 0 0
#> 180.1 14.82 1 37 0 0
#> 76.1 19.22 1 54 0 1
#> 117 17.46 1 26 0 1
#> 181.1 16.46 1 45 0 1
#> 187.2 9.92 1 39 1 0
#> 145 10.07 1 65 1 0
#> 39 15.59 1 37 0 1
#> 45 17.42 1 54 0 1
#> 32.1 20.90 1 37 1 0
#> 113 22.86 1 34 0 0
#> 187.3 9.92 1 39 1 0
#> 66.1 22.13 1 53 0 0
#> 189 10.51 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 57.1 14.46 1 45 0 1
#> 175.2 21.91 1 43 0 0
#> 69.2 23.23 1 25 0 1
#> 43.1 12.10 1 61 0 1
#> 18 15.21 1 49 1 0
#> 150.2 20.33 1 48 0 0
#> 10.2 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 36.1 21.19 1 48 0 1
#> 5 16.43 1 51 0 1
#> 88.1 18.37 1 47 0 0
#> 90.1 20.94 1 50 0 1
#> 101.2 9.97 1 10 0 1
#> 150.3 20.33 1 48 0 0
#> 26.2 15.77 1 49 0 1
#> 37.2 12.52 1 57 1 0
#> 123 13.00 1 44 1 0
#> 127.1 3.53 1 62 0 1
#> 123.1 13.00 1 44 1 0
#> 2 24.00 0 9 0 0
#> 176 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 178 24.00 0 52 1 0
#> 112 24.00 0 61 0 0
#> 126 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 98 24.00 0 34 1 0
#> 72 24.00 0 40 0 1
#> 64 24.00 0 43 0 0
#> 3 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 161 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 53 24.00 0 32 0 1
#> 165 24.00 0 47 0 0
#> 152.1 24.00 0 36 0 1
#> 47 24.00 0 38 0 1
#> 17 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 53.1 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 178.1 24.00 0 52 1 0
#> 20 24.00 0 46 1 0
#> 178.2 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 104 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 174.1 24.00 0 49 1 0
#> 165.1 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 131.1 24.00 0 66 0 0
#> 80 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 116.1 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 116.2 24.00 0 58 0 1
#> 87 24.00 0 27 0 0
#> 28.1 24.00 0 67 1 0
#> 162 24.00 0 51 0 0
#> 147 24.00 0 76 1 0
#> 165.2 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 156 24.00 0 50 1 0
#> 34.1 24.00 0 36 0 0
#> 147.1 24.00 0 76 1 0
#> 116.3 24.00 0 58 0 1
#> 12 24.00 0 63 0 0
#> 135 24.00 0 58 1 0
#> 160.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 104.1 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 174.2 24.00 0 49 1 0
#> 141 24.00 0 44 1 0
#> 80.1 24.00 0 41 0 0
#> 98.1 24.00 0 34 1 0
#> 141.1 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 109.1 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 146.1 24.00 0 63 1 0
#> 115 24.00 0 NA 1 0
#> 1 24.00 0 23 1 0
#> 19.1 24.00 0 57 0 1
#> 95 24.00 0 68 0 1
#> 64.1 24.00 0 43 0 0
#> 46.1 24.00 0 71 0 0
#> 141.2 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 2.1 24.00 0 9 0 0
#> 98.2 24.00 0 34 1 0
#> 146.2 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 156.1 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.362 NA NA NA
#> 2 age, Cure model -0.00791 NA NA NA
#> 3 grade_ii, Cure model -0.116 NA NA NA
#> 4 grade_iii, Cure model 0.762 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0109 NA NA NA
#> 2 grade_ii, Survival model 0.651 NA NA NA
#> 3 grade_iii, Survival model 0.136 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.361622 -0.007913 -0.115853 0.761992
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 255.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.361621614 -0.007912597 -0.115853291 0.761992223
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01089215 0.65143986 0.13604953
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.94566602 0.89171849 0.38571101 0.87114487 0.98232311 0.52912606
#> [7] 0.94566602 0.15636573 0.75493857 0.55796163 0.53904310 0.68038665
#> [13] 0.06405064 0.85543001 0.59427472 0.87114487 0.29000382 0.79799100
#> [19] 0.97781904 0.65042040 0.81576905 0.70855444 0.96870716 0.59427472
#> [25] 0.84431720 0.47931594 0.45777613 0.75493857 0.32487227 0.83299798
#> [31] 0.65807462 0.68038665 0.90675627 0.93126356 0.85543001 0.38571101
#> [37] 0.70855444 0.24916237 0.80404369 0.99121085 0.37141371 0.11978525
#> [43] 0.93126356 0.63483972 0.47931594 0.38571101 0.27008431 0.15636573
#> [49] 0.78589054 0.43415842 0.84989655 0.88660255 0.90177982 0.98232311
#> [55] 0.90675627 0.56729099 0.96409852 0.68038665 0.87114487 0.32487227
#> [61] 0.58540143 0.80404369 0.66563729 0.77973401 0.61091913 0.76738599
#> [67] 0.83299798 0.92149566 0.61091913 0.97327778 0.51903458 0.76738599
#> [73] 0.53904310 0.62686738 0.66563729 0.94566602 0.92641686 0.73555929
#> [79] 0.64268025 0.45777613 0.22478773 0.94566602 0.29000382 0.74217600
#> [85] 0.78589054 0.32487227 0.15636573 0.89171849 0.74861905 0.47931594
#> [91] 0.90675627 0.72889979 0.38571101 0.70151196 0.56729099 0.43415842
#> [97] 0.93126356 0.47931594 0.70855444 0.85543001 0.82163909 0.99121085
#> [103] 0.82163909 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 187 43 99 56 91 105 187.1 69 157 97 76 85 78
#> 9.92 12.10 21.19 12.21 5.33 19.75 9.92 23.23 15.10 19.14 19.22 16.44 23.88
#> 37 41 56.1 66 81 25 23 155 26 149 41.1 140 150
#> 12.52 18.02 12.21 22.13 14.06 6.32 16.92 13.08 15.77 8.37 18.02 12.68 20.33
#> 32 157.1 175 14 130 192 10 101 37.1 36 26.1 63 60
#> 20.90 15.10 21.91 12.89 16.47 16.44 10.53 9.97 12.52 21.19 15.77 22.77 13.15
#> 127 197 86 101.1 30 150.1 99.1 169 69.1 57 90 177 49
#> 3.53 21.60 23.81 9.97 17.43 20.33 21.19 22.41 23.23 14.46 20.94 12.53 12.19
#> 107 91.1 10.1 88 16 192.1 56.2 175.1 51 60.1 181 133 40
#> 11.18 5.33 10.53 18.37 8.71 16.44 12.21 21.91 18.23 13.15 16.46 14.65 18.00
#> 180 14.1 61 40.1 77 166 180.1 76.1 117 181.1 187.2 145 39
#> 14.82 12.89 10.12 18.00 7.27 19.98 14.82 19.22 17.46 16.46 9.92 10.07 15.59
#> 45 32.1 113 187.3 66.1 29 57.1 175.2 69.2 43.1 18 150.2 10.2
#> 17.42 20.90 22.86 9.92 22.13 15.45 14.46 21.91 23.23 12.10 15.21 20.33 10.53
#> 125 36.1 5 88.1 90.1 101.2 150.3 26.2 37.2 123 127.1 123.1 2
#> 15.65 21.19 16.43 18.37 20.94 9.97 20.33 15.77 12.52 13.00 3.53 13.00 24.00
#> 176 152 178 112 126 31 44 186 116 98 72 64 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 161 131 46 53 165 152.1 47 17 174 53.1 122 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 182 178.1 20 178.2 54 104 28 174.1 165.1 34 131.1 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82 116.1 160 67 151 146 116.2 87 28.1 162 147 165.2 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 34.1 147.1 116.3 12 135 160.1 102 104.1 109 142 174.2 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80.1 98.1 141.1 185 19 109.1 172 146.1 1 19.1 95 64.1 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.2 67.1 200 2.1 98.2 146.2 82.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[37]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004163152 0.695691677 0.380797532
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05487093 0.01884412 0.25187602
#> grade_iii, Cure model
#> 0.89070539
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 127 3.53 1 62 0 1
#> 123 13.00 1 44 1 0
#> 59 10.16 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 6 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 78 23.88 1 43 0 0
#> 105 19.75 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 180 14.82 1 37 0 0
#> 188 16.16 1 46 0 1
#> 125 15.65 1 67 1 0
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 45 17.42 1 54 0 1
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 164 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 177 12.53 1 75 0 0
#> 15 22.68 1 48 0 0
#> 134.1 17.81 1 47 1 0
#> 136 21.83 1 43 0 1
#> 40 18.00 1 28 1 0
#> 60 13.15 1 38 1 0
#> 127.1 3.53 1 62 0 1
#> 157 15.10 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 59.1 10.16 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 58.1 19.34 1 39 0 0
#> 164.2 23.60 1 76 0 1
#> 149 8.37 1 33 1 0
#> 66.1 22.13 1 53 0 0
#> 51.2 18.23 1 83 0 1
#> 183 9.24 1 67 1 0
#> 177.1 12.53 1 75 0 0
#> 43 12.10 1 61 0 1
#> 190 20.81 1 42 1 0
#> 50 10.02 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 97 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 184 17.77 1 38 0 0
#> 58.2 19.34 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 110 17.56 1 65 0 1
#> 55 19.34 1 69 0 1
#> 5 16.43 1 51 0 1
#> 66.2 22.13 1 53 0 0
#> 41 18.02 1 40 1 0
#> 127.2 3.53 1 62 0 1
#> 97.1 19.14 1 65 0 1
#> 99 21.19 1 38 0 1
#> 91 5.33 1 61 0 1
#> 15.1 22.68 1 48 0 0
#> 43.1 12.10 1 61 0 1
#> 113 22.86 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 158 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 150 20.33 1 48 0 0
#> 10 10.53 1 34 0 0
#> 170 19.54 1 43 0 1
#> 93 10.33 1 52 0 1
#> 170.1 19.54 1 43 0 1
#> 90 20.94 1 50 0 1
#> 114.1 13.68 1 NA 0 0
#> 171.1 16.57 1 41 0 1
#> 157.1 15.10 1 47 0 0
#> 4 17.64 1 NA 0 1
#> 52 10.42 1 52 0 1
#> 99.1 21.19 1 38 0 1
#> 76 19.22 1 54 0 1
#> 49 12.19 1 48 1 0
#> 124 9.73 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 96 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 105.2 19.75 1 60 0 0
#> 78.1 23.88 1 43 0 0
#> 107.1 11.18 1 54 1 0
#> 81 14.06 1 34 0 0
#> 8.2 18.43 1 32 0 0
#> 123.1 13.00 1 44 1 0
#> 111 17.45 1 47 0 1
#> 125.1 15.65 1 67 1 0
#> 192 16.44 1 31 1 0
#> 134.2 17.81 1 47 1 0
#> 13 14.34 1 54 0 1
#> 181.1 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 128 20.35 1 35 0 1
#> 133 14.65 1 57 0 0
#> 171.2 16.57 1 41 0 1
#> 149.1 8.37 1 33 1 0
#> 8.3 18.43 1 32 0 0
#> 18 15.21 1 49 1 0
#> 43.2 12.10 1 61 0 1
#> 40.1 18.00 1 28 1 0
#> 184.2 17.77 1 38 0 0
#> 55.1 19.34 1 69 0 1
#> 136.1 21.83 1 43 0 1
#> 149.2 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 199 19.81 1 NA 0 1
#> 173 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 178 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 98 24.00 0 34 1 0
#> 176 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 138 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 162 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 98.1 24.00 0 34 1 0
#> 35 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 38 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 83.1 24.00 0 6 0 0
#> 172.1 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 200 24.00 0 64 0 0
#> 3 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 115.2 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 119 24.00 0 17 0 0
#> 200.1 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 83.2 24.00 0 6 0 0
#> 198 24.00 0 66 0 1
#> 102 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 141 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 162.1 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 148 24.00 0 61 1 0
#> 200.2 24.00 0 64 0 0
#> 135 24.00 0 58 1 0
#> 156 24.00 0 50 1 0
#> 112.1 24.00 0 61 0 0
#> 116 24.00 0 58 0 1
#> 19 24.00 0 57 0 1
#> 12 24.00 0 63 0 0
#> 94.1 24.00 0 51 0 1
#> 17.1 24.00 0 38 0 1
#> 72.1 24.00 0 40 0 1
#> 82 24.00 0 34 0 0
#> 75 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 35.1 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 64.1 24.00 0 43 0 0
#> 102.1 24.00 0 49 0 0
#> 19.1 24.00 0 57 0 1
#> 53 24.00 0 32 0 1
#> 176.1 24.00 0 43 0 1
#> 163 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 87 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#> 11 24.00 0 42 0 1
#> 116.1 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 87.1 24.00 0 27 0 0
#> 200.3 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 176.2 24.00 0 43 0 1
#> 162.2 24.00 0 51 0 0
#> 87.2 24.00 0 27 0 0
#> 165.1 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 33.1 24.00 0 53 0 0
#> 102.2 24.00 0 49 0 0
#> 21.1 24.00 0 47 0 0
#> 141.1 24.00 0 44 1 0
#> 94.2 24.00 0 51 0 1
#> 112.2 24.00 0 61 0 0
#> 165.2 24.00 0 47 0 0
#> 103.2 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.05 NA NA NA
#> 2 age, Cure model 0.0188 NA NA NA
#> 3 grade_ii, Cure model 0.252 NA NA NA
#> 4 grade_iii, Cure model 0.891 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00416 NA NA NA
#> 2 grade_ii, Survival model 0.696 NA NA NA
#> 3 grade_iii, Survival model 0.381 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05487 0.01884 0.25188 0.89071
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 247.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05487093 0.01884412 0.25187602 0.89070539
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004163152 0.695691677 0.380797532
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.95015040 0.97519737 0.80381330 0.70521915 0.25347474 0.01091042
#> [7] 0.26370147 0.26370147 0.31417738 0.74993409 0.66913515 0.68737074
#> [13] 0.44288584 0.44288584 0.58636376 0.50239949 0.39296130 0.03608067
#> [19] 0.11305756 0.82128531 0.09083769 0.50239949 0.14660349 0.48305259
#> [25] 0.79489886 0.97519737 0.73207912 0.03608067 0.16912878 0.40315318
#> [31] 0.31417738 0.03608067 0.92519330 0.11305756 0.44288584 0.91662391
#> [37] 0.82128531 0.84763094 0.21228979 0.64174906 0.37292417 0.67826480
#> [43] 0.59579850 0.53011091 0.31417738 0.70521915 0.95015040 0.55803622
#> [49] 0.31417738 0.65997948 0.11305756 0.47296002 0.97519737 0.37292417
#> [55] 0.18037341 0.96683073 0.09083769 0.84763094 0.06679005 0.40315318
#> [61] 0.24332225 0.87357176 0.23296526 0.89074688 0.29395834 0.90801291
#> [67] 0.29395834 0.20152835 0.59579850 0.73207912 0.89938729 0.18037341
#> [73] 0.36270256 0.83885760 0.53011091 0.76794997 0.62335590 0.26370147
#> [79] 0.01091042 0.87357176 0.78591271 0.40315318 0.80381330 0.56748572
#> [85] 0.68737074 0.64174906 0.50239949 0.77694010 0.62335590 0.07950165
#> [91] 0.22269105 0.75893073 0.59579850 0.92519330 0.40315318 0.72313554
#> [97] 0.84763094 0.48305259 0.53011091 0.31417738 0.14660349 0.92519330
#> [103] 0.57690333 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 77 127 123 6 166 78 105 105.1 58 180 188 125 51
#> 7.27 3.53 13.00 15.64 19.98 23.88 19.75 19.75 19.34 14.82 16.16 15.65 18.23
#> 51.1 45 134 179 164 66 177 15 134.1 136 40 60 127.1
#> 18.23 17.42 17.81 18.63 23.60 22.13 12.53 22.68 17.81 21.83 18.00 13.15 3.53
#> 157 164.1 139 8 58.1 164.2 149 66.1 51.2 183 177.1 43 190
#> 15.10 23.60 21.49 18.43 19.34 23.60 8.37 22.13 18.23 9.24 12.53 12.10 20.81
#> 85 97 26 171 184 58.2 6.1 77.1 110 55 5 66.2 41
#> 16.44 19.14 15.77 16.57 17.77 19.34 15.64 7.27 17.56 19.34 16.43 22.13 18.02
#> 127.2 97.1 99 91 15.1 43.1 113 8.1 158 107 150 10 170
#> 3.53 19.14 21.19 5.33 22.68 12.10 22.86 18.43 20.14 11.18 20.33 10.53 19.54
#> 93 170.1 90 171.1 157.1 52 99.1 76 49 184.1 96 181 105.2
#> 10.33 19.54 20.94 16.57 15.10 10.42 21.19 19.22 12.19 17.77 14.54 16.46 19.75
#> 78.1 107.1 81 8.2 123.1 111 125.1 192 134.2 13 181.1 63 128
#> 23.88 11.18 14.06 18.43 13.00 17.45 15.65 16.44 17.81 14.34 16.46 22.77 20.35
#> 133 171.2 149.1 8.3 18 43.2 40.1 184.2 55.1 136.1 149.2 30 173
#> 14.65 16.57 8.37 18.43 15.21 12.10 18.00 17.77 19.34 21.83 8.37 17.43 24.00
#> 112 178 33 98 176 138 142 162 83 17 186 98.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 1 172 38 174 83.1 172.1 143 200 3 151 72 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200.1 7 83.2 198 102 185 141 103 162.1 94 148 200.2 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 112.1 116 19 12 94.1 17.1 72.1 82 75 46 80 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 165 64.1 102.1 19.1 53 176.1 163 48 118 142.1 87 103.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 116.1 53.1 87.1 200.3 21 176.2 162.2 87.2 165.1 62 33.1 102.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.1 141.1 94.2 112.2 165.2 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[38]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.006334644 0.628514243 0.392262710
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.306537603 0.007235933 -0.135207641
#> grade_iii, Cure model
#> 0.547059076
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 77 7.27 1 67 0 1
#> 128 20.35 1 35 0 1
#> 153 21.33 1 55 1 0
#> 68 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 127 3.53 1 62 0 1
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 134 17.81 1 47 1 0
#> 145 10.07 1 65 1 0
#> 155 13.08 1 26 0 0
#> 25 6.32 1 34 1 0
#> 52 10.42 1 52 0 1
#> 77.1 7.27 1 67 0 1
#> 50 10.02 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 194 22.40 1 38 0 1
#> 58 19.34 1 39 0 0
#> 168 23.72 1 70 0 0
#> 49 12.19 1 48 1 0
#> 179 18.63 1 42 0 0
#> 181 16.46 1 45 0 1
#> 60.1 13.15 1 38 1 0
#> 25.1 6.32 1 34 1 0
#> 86 23.81 1 58 0 1
#> 78 23.88 1 43 0 0
#> 69 23.23 1 25 0 1
#> 140.1 12.68 1 59 1 0
#> 139 21.49 1 63 1 0
#> 58.1 19.34 1 39 0 0
#> 37 12.52 1 57 1 0
#> 10 10.53 1 34 0 0
#> 4 17.64 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 133 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 164 23.60 1 76 0 1
#> 70 7.38 1 30 1 0
#> 96 14.54 1 33 0 1
#> 49.1 12.19 1 48 1 0
#> 154 12.63 1 20 1 0
#> 37.1 12.52 1 57 1 0
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 181.1 16.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 51 18.23 1 83 0 1
#> 96.1 14.54 1 33 0 1
#> 99 21.19 1 38 0 1
#> 150 20.33 1 48 0 0
#> 88 18.37 1 47 0 0
#> 124 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 36 21.19 1 48 0 1
#> 92 22.92 1 47 0 1
#> 63 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 133.1 14.65 1 57 0 0
#> 170 19.54 1 43 0 1
#> 110 17.56 1 65 0 1
#> 180 14.82 1 37 0 0
#> 93 10.33 1 52 0 1
#> 114 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 85 16.44 1 36 0 0
#> 100 16.07 1 60 0 0
#> 58.2 19.34 1 39 0 0
#> 129.1 23.41 1 53 1 0
#> 4.1 17.64 1 NA 0 1
#> 13 14.34 1 54 0 1
#> 76 19.22 1 54 0 1
#> 91 5.33 1 61 0 1
#> 168.1 23.72 1 70 0 0
#> 179.1 18.63 1 42 0 0
#> 199.1 19.81 1 NA 0 1
#> 194.1 22.40 1 38 0 1
#> 5 16.43 1 51 0 1
#> 50.1 10.02 1 NA 1 0
#> 42.1 12.43 1 49 0 1
#> 189 10.51 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 68.1 20.62 1 44 0 0
#> 43.2 12.10 1 61 0 1
#> 8 18.43 1 32 0 0
#> 58.3 19.34 1 39 0 0
#> 36.1 21.19 1 48 0 1
#> 117 17.46 1 26 0 1
#> 45.1 17.42 1 54 0 1
#> 166.1 19.98 1 48 0 0
#> 149 8.37 1 33 1 0
#> 36.2 21.19 1 48 0 1
#> 179.2 18.63 1 42 0 0
#> 40 18.00 1 28 1 0
#> 5.1 16.43 1 51 0 1
#> 139.1 21.49 1 63 1 0
#> 16 8.71 1 71 0 1
#> 155.1 13.08 1 26 0 0
#> 190 20.81 1 42 1 0
#> 50.2 10.02 1 NA 1 0
#> 60.2 13.15 1 38 1 0
#> 150.1 20.33 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 150.2 20.33 1 48 0 0
#> 149.1 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 18 15.21 1 49 1 0
#> 40.1 18.00 1 28 1 0
#> 177 12.53 1 75 0 0
#> 161 24.00 0 45 0 0
#> 156 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 141 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 11 24.00 0 42 0 1
#> 33 24.00 0 53 0 0
#> 152 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 118 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 48.1 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 74 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 142 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 141.1 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 143 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 191.1 24.00 0 60 0 1
#> 156.1 24.00 0 50 1 0
#> 94 24.00 0 51 0 1
#> 21.1 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 191.2 24.00 0 60 0 1
#> 87 24.00 0 27 0 0
#> 174.1 24.00 0 49 1 0
#> 162 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 33.1 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 33.2 24.00 0 53 0 0
#> 44 24.00 0 56 0 0
#> 9.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 178.1 24.00 0 52 1 0
#> 62 24.00 0 71 0 0
#> 17.1 24.00 0 38 0 1
#> 120.1 24.00 0 68 0 1
#> 31.2 24.00 0 36 0 1
#> 156.2 24.00 0 50 1 0
#> 116 24.00 0 58 0 1
#> 73 24.00 0 NA 0 1
#> 48.2 24.00 0 31 1 0
#> 21.2 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 143.1 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 115 24.00 0 NA 1 0
#> 22.1 24.00 0 52 1 0
#> 48.3 24.00 0 31 1 0
#> 21.3 24.00 0 47 0 0
#> 112.1 24.00 0 61 0 0
#> 17.2 24.00 0 38 0 1
#> 47.2 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 19 24.00 0 57 0 1
#> 185.1 24.00 0 44 1 0
#> 185.2 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 44.1 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 65 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 141.2 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 143.2 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 152.1 24.00 0 36 0 1
#> 44.2 24.00 0 56 0 0
#> 118.1 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.307 NA NA NA
#> 2 age, Cure model 0.00724 NA NA NA
#> 3 grade_ii, Cure model -0.135 NA NA NA
#> 4 grade_iii, Cure model 0.547 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00633 NA NA NA
#> 2 grade_ii, Survival model 0.629 NA NA NA
#> 3 grade_iii, Survival model 0.392 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.306538 0.007236 -0.135208 0.547059
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 253.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.306537603 0.007235933 -0.135207641 0.547059076
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.006334644 0.628514243 0.392262710
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.945064306 0.251741658 0.177261971 0.232840628 0.717737324 0.990845566
#> [7] 0.289763053 0.470556366 0.879787453 0.688462299 0.963466766 0.860771427
#> [13] 0.945064306 0.659602287 0.137061181 0.319339824 0.034130503 0.794646038
#> [19] 0.378597873 0.520546609 0.659602287 0.963466766 0.023052400 0.006200756
#> [25] 0.092952157 0.717737324 0.157490070 0.319339824 0.756433205 0.851253222
#> [31] 0.889267309 0.609883640 0.580036083 0.057519222 0.935823571 0.629819191
#> [37] 0.794646038 0.737080348 0.756433205 0.775559686 0.126161562 0.889267309
#> [43] 0.520546609 0.500735607 0.440022875 0.629819191 0.187254847 0.261308515
#> [49] 0.419178669 0.071008146 0.187254847 0.104287744 0.115503770 0.841755595
#> [55] 0.609883640 0.309400797 0.480630927 0.599932478 0.870282809 0.368444011
#> [61] 0.813558319 0.813558319 0.540272757 0.570017454 0.319339824 0.071008146
#> [67] 0.649628724 0.358295563 0.981691175 0.034130503 0.378597873 0.137061181
#> [73] 0.550265090 0.775559686 0.707922499 0.232840628 0.813558319 0.408803376
#> [79] 0.319339824 0.187254847 0.490709573 0.500735607 0.289763053 0.917333367
#> [85] 0.187254847 0.378597873 0.450456066 0.550265090 0.157490070 0.907942055
#> [91] 0.688462299 0.223381264 0.659602287 0.261308515 0.006200756 0.261308515
#> [97] 0.917333367 0.429620521 0.590015689 0.450456066 0.746733066 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 77 128 153 68 140 127 166 134 145 155 25 52 77.1
#> 7.27 20.35 21.33 20.62 12.68 3.53 19.98 17.81 10.07 13.08 6.32 10.42 7.27
#> 60 194 58 168 49 179 181 60.1 25.1 86 78 69 140.1
#> 13.15 22.40 19.34 23.72 12.19 18.63 16.46 13.15 6.32 23.81 23.88 23.23 12.68
#> 139 58.1 37 10 187 133 125 164 70 96 49.1 154 37.1
#> 21.49 19.34 12.52 10.53 9.92 14.65 15.65 23.60 7.38 14.54 12.19 12.63 12.52
#> 42 15 187.1 181.1 45 51 96.1 99 150 88 129 36 92
#> 12.43 22.68 9.92 16.46 17.42 18.23 14.54 21.19 20.33 18.37 23.41 21.19 22.92
#> 63 159 133.1 170 110 180 93 97 43 43.1 85 100 58.2
#> 22.77 10.55 14.65 19.54 17.56 14.82 10.33 19.14 12.10 12.10 16.44 16.07 19.34
#> 129.1 13 76 91 168.1 179.1 194.1 5 42.1 14 68.1 43.2 8
#> 23.41 14.34 19.22 5.33 23.72 18.63 22.40 16.43 12.43 12.89 20.62 12.10 18.43
#> 58.3 36.1 117 45.1 166.1 149 36.2 179.2 40 5.1 139.1 16 155.1
#> 19.34 21.19 17.46 17.42 19.98 8.37 21.19 18.63 18.00 16.43 21.49 8.71 13.08
#> 190 60.2 150.1 78.1 150.2 149.1 108 18 40.1 177 161 156 185
#> 20.81 13.15 20.33 23.88 20.33 8.37 18.29 15.21 18.00 12.53 24.00 24.00 24.00
#> 112 17 31 22 9 174 141 21 172 2 11 33 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 1 118 147 48 191 48.1 75 74 120 186 47 142
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 141.1 75.1 143 137 191.1 156.1 94 21.1 178 191.2 87 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 47.1 33.1 31.1 33.2 44 9.1 72 178.1 62 17.1 120.1 31.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 116 48.2 21.2 122 143.1 161.1 22.1 48.3 21.3 112.1 17.2 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 19 185.1 185.2 27 44.1 160 12 65 151 141.2 7 143.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 152.1 44.2 118.1 7.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[39]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01221415 0.23371902 0.09989443
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.77416021 0.02809218 0.56343881
#> grade_iii, Cure model
#> 1.40261192
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 124 9.73 1 NA 1 0
#> 154 12.63 1 20 1 0
#> 66 22.13 1 53 0 0
#> 63 22.77 1 31 1 0
#> 154.1 12.63 1 20 1 0
#> 36 21.19 1 48 0 1
#> 55 19.34 1 69 0 1
#> 100 16.07 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 139 21.49 1 63 1 0
#> 150 20.33 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 139.1 21.49 1 63 1 0
#> 133 14.65 1 57 0 0
#> 125 15.65 1 67 1 0
#> 169 22.41 1 46 0 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 166 19.98 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 13 14.34 1 54 0 1
#> 130 16.47 1 53 0 1
#> 61 10.12 1 36 0 1
#> 42 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 50.1 10.02 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 93 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 99 21.19 1 38 0 1
#> 179.1 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 157 15.10 1 47 0 0
#> 187 9.92 1 39 1 0
#> 110 17.56 1 65 0 1
#> 56 12.21 1 60 0 0
#> 157.1 15.10 1 47 0 0
#> 136 21.83 1 43 0 1
#> 32 20.90 1 37 1 0
#> 110.1 17.56 1 65 0 1
#> 5 16.43 1 51 0 1
#> 8 18.43 1 32 0 0
#> 58 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 15 22.68 1 48 0 0
#> 79 16.23 1 54 1 0
#> 96.1 14.54 1 33 0 1
#> 125.1 15.65 1 67 1 0
#> 145 10.07 1 65 1 0
#> 108 18.29 1 39 0 1
#> 97 19.14 1 65 0 1
#> 192 16.44 1 31 1 0
#> 107 11.18 1 54 1 0
#> 45 17.42 1 54 0 1
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 86 23.81 1 58 0 1
#> 136.1 21.83 1 43 0 1
#> 101 9.97 1 10 0 1
#> 100.1 16.07 1 60 0 0
#> 123 13.00 1 44 1 0
#> 145.1 10.07 1 65 1 0
#> 93.1 10.33 1 52 0 1
#> 89 11.44 1 NA 0 0
#> 190 20.81 1 42 1 0
#> 154.2 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 55.1 19.34 1 69 0 1
#> 117 17.46 1 26 0 1
#> 99.1 21.19 1 38 0 1
#> 5.1 16.43 1 51 0 1
#> 8.1 18.43 1 32 0 0
#> 171 16.57 1 41 0 1
#> 107.1 11.18 1 54 1 0
#> 23 16.92 1 61 0 0
#> 8.2 18.43 1 32 0 0
#> 79.1 16.23 1 54 1 0
#> 36.1 21.19 1 48 0 1
#> 52 10.42 1 52 0 1
#> 56.1 12.21 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 189 10.51 1 NA 1 0
#> 183 9.24 1 67 1 0
#> 114.1 13.68 1 NA 0 0
#> 139.2 21.49 1 63 1 0
#> 101.1 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 166.1 19.98 1 48 0 0
#> 91 5.33 1 61 0 1
#> 101.2 9.97 1 10 0 1
#> 77 7.27 1 67 0 1
#> 110.2 17.56 1 65 0 1
#> 51 18.23 1 83 0 1
#> 166.2 19.98 1 48 0 0
#> 159 10.55 1 50 0 1
#> 79.2 16.23 1 54 1 0
#> 188.1 16.16 1 46 0 1
#> 18.1 15.21 1 49 1 0
#> 25 6.32 1 34 1 0
#> 30.1 17.43 1 78 0 0
#> 43.1 12.10 1 61 0 1
#> 50.2 10.02 1 NA 1 0
#> 123.1 13.00 1 44 1 0
#> 170 19.54 1 43 0 1
#> 190.1 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 65 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 94 24.00 0 51 0 1
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 176 24.00 0 43 0 1
#> 143 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 75 24.00 0 21 1 0
#> 94.1 24.00 0 51 0 1
#> 75.1 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 146 24.00 0 63 1 0
#> 118 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 161 24.00 0 45 0 0
#> 74 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 71.1 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 146.1 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 102 24.00 0 49 0 0
#> 193 24.00 0 45 0 1
#> 53 24.00 0 32 0 1
#> 142 24.00 0 53 0 0
#> 137 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 160.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 116 24.00 0 58 0 1
#> 126 24.00 0 48 0 0
#> 191.1 24.00 0 60 0 1
#> 73 24.00 0 NA 0 1
#> 178 24.00 0 52 1 0
#> 35 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 132 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 84 24.00 0 39 0 1
#> 119.1 24.00 0 17 0 0
#> 21.1 24.00 0 47 0 0
#> 142.1 24.00 0 53 0 0
#> 98.1 24.00 0 34 1 0
#> 3 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 31.1 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 162.1 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 178.1 24.00 0 52 1 0
#> 173.1 24.00 0 19 0 1
#> 162.2 24.00 0 51 0 0
#> 196 24.00 0 19 0 0
#> 17.1 24.00 0 38 0 1
#> 48 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 148.1 24.00 0 61 1 0
#> 7 24.00 0 37 1 0
#> 83 24.00 0 6 0 0
#> 142.2 24.00 0 53 0 0
#> 196.1 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 65.1 24.00 0 57 1 0
#> 165.2 24.00 0 47 0 0
#> 75.2 24.00 0 21 1 0
#> 119.2 24.00 0 17 0 0
#> 83.1 24.00 0 6 0 0
#> 119.3 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 182 24.00 0 35 0 0
#> 185 24.00 0 44 1 0
#> 48.1 24.00 0 31 1 0
#> 143.1 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.77 NA NA NA
#> 2 age, Cure model 0.0281 NA NA NA
#> 3 grade_ii, Cure model 0.563 NA NA NA
#> 4 grade_iii, Cure model 1.40 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0122 NA NA NA
#> 2 grade_ii, Survival model 0.234 NA NA NA
#> 3 grade_iii, Survival model 0.0999 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.77416 0.02809 0.56344 1.40261
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.8
#> Residual Deviance: 235.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.77416021 0.02809218 0.56343881 1.40261192
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01221415 0.23371902 0.09989443
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6203490448 0.0160324049 0.0070205495 0.6203490448 0.0456479636
#> [6] 0.1290899121 0.4044712002 0.2548363493 0.0319199551 0.0891601458
#> [11] 0.9377758807 0.0274513634 0.0319199551 0.5016612149 0.4279883071
#> [16] 0.0126753636 0.5666453755 0.7016572509 0.0954814171 0.5533765452
#> [21] 0.3056209226 0.8172059257 0.6602705968 0.1148170367 0.5145180600
#> [26] 0.7876979285 0.1591683159 0.0456479636 0.1591683159 0.0024554180
#> [31] 0.4765950484 0.9071487244 0.2178176157 0.6739660012 0.4765950484
#> [36] 0.0197634337 0.0656552005 0.2178176157 0.3269969439 0.1753374110
#> [41] 0.1290899121 0.3816437257 0.0096636014 0.3486391322 0.5145180600
#> [46] 0.4279883071 0.8321741469 0.2001092143 0.1512014250 0.3162845559
#> [51] 0.7298780830 0.2745335310 0.0008858866 0.0830317164 0.0001410153
#> [56] 0.0197634337 0.8623020976 0.4044712002 0.5934597245 0.8321741469
#> [61] 0.7876979285 0.0714569644 0.6203490448 0.4520919198 0.1290899121
#> [66] 0.2452541640 0.0456479636 0.3269969439 0.1753374110 0.2951118946
#> [71] 0.7298780830 0.2847250536 0.1753374110 0.3486391322 0.0456479636
#> [76] 0.7730330312 0.6739660012 0.5800206555 0.9224060289 0.0319199551
#> [81] 0.8623020976 0.0045143153 0.0954814171 0.9843024445 0.8623020976
#> [86] 0.9531850810 0.2178176157 0.2088509914 0.0954814171 0.7584825459
#> [91] 0.3486391322 0.3816437257 0.4520919198 0.9687230157 0.2548363493
#> [96] 0.7016572509 0.5934597245 0.1218810627 0.0714569644 0.5402426998
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000
#>
#> $Time
#> 154 66 63 154.1 36 55 100 30 139 150 149 197 139.1
#> 12.63 22.13 22.77 12.63 21.19 19.34 16.07 17.43 21.49 20.33 8.37 21.60 21.49
#> 133 125 169 81 43 166 13 130 61 42 105 96 93
#> 14.65 15.65 22.41 14.06 12.10 19.98 14.34 16.47 10.12 12.43 19.75 14.54 10.33
#> 179 99 179.1 129 157 187 110 56 157.1 136 32 110.1 5
#> 18.63 21.19 18.63 23.41 15.10 9.92 17.56 12.21 15.10 21.83 20.90 17.56 16.43
#> 8 58 188 15 79 96.1 125.1 145 108 97 192 107 45
#> 18.43 19.34 16.16 22.68 16.23 14.54 15.65 10.07 18.29 19.14 16.44 11.18 17.42
#> 164 128 86 136.1 101 100.1 123 145.1 93.1 190 154.2 18 55.1
#> 23.60 20.35 23.81 21.83 9.97 16.07 13.00 10.07 10.33 20.81 12.63 15.21 19.34
#> 117 99.1 5.1 8.1 171 107.1 23 8.2 79.1 36.1 52 56.1 60
#> 17.46 21.19 16.43 18.43 16.57 11.18 16.92 18.43 16.23 21.19 10.42 12.21 13.15
#> 183 139.2 101.1 92 166.1 91 101.2 77 110.2 51 166.2 159 79.2
#> 9.24 21.49 9.97 22.92 19.98 5.33 9.97 7.27 17.56 18.23 19.98 10.55 16.23
#> 188.1 18.1 25 30.1 43.1 123.1 170 190.1 57 65 138 94 173
#> 16.16 15.21 6.32 17.43 12.10 13.00 19.54 20.81 14.46 24.00 24.00 24.00 24.00
#> 46 176 143 160 148 75 94.1 75.1 191 146 118 165 71
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 161 74 152 71.1 21 165.1 98 146.1 119 102 193 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 137 162 163 160.1 186 116 126 191.1 178 35 104 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 84 119.1 21.1 142.1 98.1 3 12 31.1 17 2 162.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 173.1 162.2 196 17.1 48 112 148.1 7 83 142.2 196.1 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 165.2 75.2 119.2 83.1 119.3 147 182 185 48.1 143.1 3.1 48.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 44 144 62
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[40]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003012146 0.546254070 0.576654308
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.395158286 0.009543584 -0.049728746
#> grade_iii, Cure model
#> 0.653377061
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 184 17.77 1 38 0 0
#> 107 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 123 13.00 1 44 1 0
#> 6 15.64 1 39 0 0
#> 117 17.46 1 26 0 1
#> 100 16.07 1 60 0 0
#> 157 15.10 1 47 0 0
#> 145 10.07 1 65 1 0
#> 167 15.55 1 56 1 0
#> 6.1 15.64 1 39 0 0
#> 155 13.08 1 26 0 0
#> 63 22.77 1 31 1 0
#> 43.1 12.10 1 61 0 1
#> 49 12.19 1 48 1 0
#> 184.1 17.77 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 159 10.55 1 50 0 1
#> 190 20.81 1 42 1 0
#> 177 12.53 1 75 0 0
#> 190.1 20.81 1 42 1 0
#> 183 9.24 1 67 1 0
#> 58 19.34 1 39 0 0
#> 29 15.45 1 68 1 0
#> 15 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 154 12.63 1 20 1 0
#> 123.1 13.00 1 44 1 0
#> 195.1 11.76 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 30 17.43 1 78 0 0
#> 93 10.33 1 52 0 1
#> 168 23.72 1 70 0 0
#> 134.1 17.81 1 47 1 0
#> 50.1 10.02 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 180 14.82 1 37 0 0
#> 51 18.23 1 83 0 1
#> 113 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 42 12.43 1 49 0 1
#> 101 9.97 1 10 0 1
#> 127 3.53 1 62 0 1
#> 93.1 10.33 1 52 0 1
#> 77 7.27 1 67 0 1
#> 40 18.00 1 28 1 0
#> 128 20.35 1 35 0 1
#> 5 16.43 1 51 0 1
#> 128.1 20.35 1 35 0 1
#> 42.1 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 45 17.42 1 54 0 1
#> 78 23.88 1 43 0 0
#> 106.1 16.67 1 49 1 0
#> 6.2 15.64 1 39 0 0
#> 90 20.94 1 50 0 1
#> 184.2 17.77 1 38 0 0
#> 29.1 15.45 1 68 1 0
#> 24 23.89 1 38 0 0
#> 101.1 9.97 1 10 0 1
#> 134.2 17.81 1 47 1 0
#> 187 9.92 1 39 1 0
#> 88.1 18.37 1 47 0 0
#> 170.1 19.54 1 43 0 1
#> 37 12.52 1 57 1 0
#> 90.1 20.94 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 140 12.68 1 59 1 0
#> 155.1 13.08 1 26 0 0
#> 18 15.21 1 49 1 0
#> 113.1 22.86 1 34 0 0
#> 55 19.34 1 69 0 1
#> 99 21.19 1 38 0 1
#> 113.2 22.86 1 34 0 0
#> 63.2 22.77 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 43.2 12.10 1 61 0 1
#> 111 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 153.2 21.33 1 55 1 0
#> 150 20.33 1 48 0 0
#> 16 8.71 1 71 0 1
#> 117.1 17.46 1 26 0 1
#> 81 14.06 1 34 0 0
#> 181.1 16.46 1 45 0 1
#> 85 16.44 1 36 0 0
#> 157.1 15.10 1 47 0 0
#> 127.1 3.53 1 62 0 1
#> 105 19.75 1 60 0 0
#> 181.2 16.46 1 45 0 1
#> 41 18.02 1 40 1 0
#> 97 19.14 1 65 0 1
#> 68 20.62 1 44 0 0
#> 168.1 23.72 1 70 0 0
#> 155.2 13.08 1 26 0 0
#> 194 22.40 1 38 0 1
#> 199 19.81 1 NA 0 1
#> 45.1 17.42 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 133 14.65 1 57 0 0
#> 164 23.60 1 76 0 1
#> 101.2 9.97 1 10 0 1
#> 4 17.64 1 NA 0 1
#> 187.1 9.92 1 39 1 0
#> 6.3 15.64 1 39 0 0
#> 75 24.00 0 21 1 0
#> 173 24.00 0 19 0 1
#> 144 24.00 0 28 0 1
#> 67 24.00 0 25 0 0
#> 122 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 162 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 94 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 84 24.00 0 39 0 1
#> 64 24.00 0 43 0 0
#> 172 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 64.1 24.00 0 43 0 0
#> 67.1 24.00 0 25 0 0
#> 83 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 67.2 24.00 0 25 0 0
#> 147 24.00 0 76 1 0
#> 176 24.00 0 43 0 1
#> 115 24.00 0 NA 1 0
#> 62 24.00 0 71 0 0
#> 142 24.00 0 53 0 0
#> 84.1 24.00 0 39 0 1
#> 1 24.00 0 23 1 0
#> 12 24.00 0 63 0 0
#> 65 24.00 0 57 1 0
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 21 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 198 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 20.1 24.00 0 46 1 0
#> 156 24.00 0 50 1 0
#> 112.1 24.00 0 61 0 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 94.1 24.00 0 51 0 1
#> 141 24.00 0 44 1 0
#> 156.1 24.00 0 50 1 0
#> 138.1 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 94.2 24.00 0 51 0 1
#> 109 24.00 0 48 0 0
#> 34.1 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 176.1 24.00 0 43 0 1
#> 103 24.00 0 56 1 0
#> 33 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 62.1 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 2 24.00 0 9 0 0
#> 142.1 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 182 24.00 0 35 0 0
#> 9 24.00 0 31 1 0
#> 84.2 24.00 0 39 0 1
#> 152.1 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 64.2 24.00 0 43 0 0
#> 143.1 24.00 0 51 0 0
#> 103.1 24.00 0 56 1 0
#> 146.1 24.00 0 63 1 0
#> 115.1 24.00 0 NA 1 0
#> 162.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 185.1 24.00 0 44 1 0
#> 72.1 24.00 0 40 0 1
#> 1.1 24.00 0 23 1 0
#> 102 24.00 0 49 0 0
#> 53 24.00 0 32 0 1
#> 178.2 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.395 NA NA NA
#> 2 age, Cure model 0.00954 NA NA NA
#> 3 grade_ii, Cure model -0.0497 NA NA NA
#> 4 grade_iii, Cure model 0.653 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00301 NA NA NA
#> 2 grade_ii, Survival model 0.546 NA NA NA
#> 3 grade_iii, Survival model 0.577 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.395158 0.009544 -0.049729 0.653377
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 258.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.395158286 0.009543584 -0.049728746 0.653377061
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003012146 0.546254070 0.576654308
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.58575715 0.90870177 0.89068607 0.83362709 0.71976085 0.60954663
#> [7] 0.71276754 0.77421971 0.93239046 0.74719816 0.71976085 0.81403338
#> [13] 0.24554944 0.89068607 0.88449630 0.58575715 0.50085898 0.91470591
#> [19] 0.38482514 0.85936547 0.38482514 0.96670800 0.47373224 0.75408706
#> [25] 0.28746441 0.45510526 0.24554944 0.85297477 0.83362709 0.67762086
#> [31] 0.56185007 0.80083279 0.63287434 0.92066821 0.11158017 0.56185007
#> [37] 0.17750386 0.51855249 0.78750987 0.53615472 0.19612402 0.66303591
#> [43] 0.87207386 0.93822961 0.98908564 0.92066821 0.98354306 0.55340461
#> [49] 0.41582007 0.70576062 0.41582007 0.87207386 0.31598592 0.64059002
#> [55] 0.06193800 0.66303591 0.71976085 0.36311126 0.58575715 0.75408706
#> [61] 0.02538828 0.93822961 0.56185007 0.95537284 0.51855249 0.45510526
#> [67] 0.86574416 0.36311126 0.50085898 0.84654388 0.81403338 0.76752833
#> [73] 0.19612402 0.47373224 0.35132168 0.19612402 0.24554944 0.31598592
#> [79] 0.65553678 0.89068607 0.62513367 0.97796343 0.31598592 0.43540648
#> [85] 0.97235533 0.60954663 0.80743599 0.67762086 0.69867807 0.77421971
#> [91] 0.98908564 0.44527744 0.67762086 0.54484437 0.49188961 0.40542418
#> [97] 0.11158017 0.81403338 0.30206013 0.64059002 0.06193800 0.79417656
#> [103] 0.15690116 0.93822961 0.95537284 0.71976085 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 184 107 43 123 6 117 100 157 145 167 6.1 155 63
#> 17.77 11.18 12.10 13.00 15.64 17.46 16.07 15.10 10.07 15.55 15.64 13.08 22.77
#> 43.1 49 184.1 179 159 190 177 190.1 183 58 29 15 170
#> 12.10 12.19 17.77 18.63 10.55 20.81 12.53 20.81 9.24 19.34 15.45 22.68 19.54
#> 63.1 154 123.1 181 134 96 30 93 168 134.1 69 88 180
#> 22.77 12.63 13.00 16.46 17.81 14.54 17.43 10.33 23.72 17.81 23.23 18.37 14.82
#> 51 113 106 42 101 127 93.1 77 40 128 5 128.1 42.1
#> 18.23 22.86 16.67 12.43 9.97 3.53 10.33 7.27 18.00 20.35 16.43 20.35 12.43
#> 153 45 78 106.1 6.2 90 184.2 29.1 24 101.1 134.2 187 88.1
#> 21.33 17.42 23.88 16.67 15.64 20.94 17.77 15.45 23.89 9.97 17.81 9.92 18.37
#> 170.1 37 90.1 179.1 140 155.1 18 113.1 55 99 113.2 63.2 153.1
#> 19.54 12.52 20.94 18.63 12.68 13.08 15.21 22.86 19.34 21.19 22.86 22.77 21.33
#> 23 43.2 111 70 153.2 150 16 117.1 81 181.1 85 157.1 127.1
#> 16.92 12.10 17.45 7.38 21.33 20.33 8.71 17.46 14.06 16.46 16.44 15.10 3.53
#> 105 181.2 41 97 68 168.1 155.2 194 45.1 78.1 133 164 101.2
#> 19.75 16.46 18.02 19.14 20.62 23.72 13.08 22.40 17.42 23.88 14.65 23.60 9.97
#> 187.1 6.3 75 173 144 67 122 54 162 116 94 34 84
#> 9.92 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 172 151 64.1 67.1 83 20 67.2 147 176 62 142 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 12 65 138 120 152 165 72 178 54.1 21 3 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 161 198 112 20.1 156 112.1 143 87 94.1 141 156.1 138.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 98 94.2 109 34.1 71 83.1 176.1 103 33 35 185 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 62.1 82 2 142.1 75.1 182 9 84.2 152.1 104 64.2 143.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.1 146.1 162.1 17 185.1 72.1 1.1 102 53 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[41]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0100266 0.7512950 0.3226116
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.329348164 0.003450279 0.248231679
#> grade_iii, Cure model
#> 0.848154915
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 150 20.33 1 48 0 0
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 60 13.15 1 38 1 0
#> 61 10.12 1 36 0 1
#> 192 16.44 1 31 1 0
#> 43 12.10 1 61 0 1
#> 70 7.38 1 30 1 0
#> 43.1 12.10 1 61 0 1
#> 90 20.94 1 50 0 1
#> 129 23.41 1 53 1 0
#> 164 23.60 1 76 0 1
#> 60.1 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 188 16.16 1 46 0 1
#> 89 11.44 1 NA 0 0
#> 159 10.55 1 50 0 1
#> 179 18.63 1 42 0 0
#> 101 9.97 1 10 0 1
#> 195 11.76 1 NA 1 0
#> 42 12.43 1 49 0 1
#> 59 10.16 1 NA 1 0
#> 139 21.49 1 63 1 0
#> 113 22.86 1 34 0 0
#> 166 19.98 1 48 0 0
#> 25 6.32 1 34 1 0
#> 89.1 11.44 1 NA 0 0
#> 26 15.77 1 49 0 1
#> 128 20.35 1 35 0 1
#> 96 14.54 1 33 0 1
#> 175 21.91 1 43 0 0
#> 113.1 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 70.1 7.38 1 30 1 0
#> 40 18.00 1 28 1 0
#> 169 22.41 1 46 0 0
#> 79 16.23 1 54 1 0
#> 41 18.02 1 40 1 0
#> 51 18.23 1 83 0 1
#> 81 14.06 1 34 0 0
#> 8 18.43 1 32 0 0
#> 58 19.34 1 39 0 0
#> 43.2 12.10 1 61 0 1
#> 63 22.77 1 31 1 0
#> 6 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 107 11.18 1 54 1 0
#> 39 15.59 1 37 0 1
#> 114 13.68 1 NA 0 0
#> 136 21.83 1 43 0 1
#> 58.1 19.34 1 39 0 0
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 179.1 18.63 1 42 0 0
#> 88 18.37 1 47 0 0
#> 127 3.53 1 62 0 1
#> 68 20.62 1 44 0 0
#> 16 8.71 1 71 0 1
#> 125 15.65 1 67 1 0
#> 56.1 12.21 1 60 0 0
#> 154 12.63 1 20 1 0
#> 59.1 10.16 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 175.1 21.91 1 43 0 0
#> 36.1 21.19 1 48 0 1
#> 30 17.43 1 78 0 0
#> 78 23.88 1 43 0 0
#> 154.1 12.63 1 20 1 0
#> 14 12.89 1 21 0 0
#> 76.1 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 49 12.19 1 48 1 0
#> 111 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 197 21.60 1 69 1 0
#> 49.1 12.19 1 48 1 0
#> 195.1 11.76 1 NA 1 0
#> 89.2 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 86 23.81 1 58 0 1
#> 16.1 8.71 1 71 0 1
#> 155 13.08 1 26 0 0
#> 166.1 19.98 1 48 0 0
#> 170 19.54 1 43 0 1
#> 100 16.07 1 60 0 0
#> 23 16.92 1 61 0 0
#> 153 21.33 1 55 1 0
#> 36.2 21.19 1 48 0 1
#> 86.1 23.81 1 58 0 1
#> 51.2 18.23 1 83 0 1
#> 145 10.07 1 65 1 0
#> 99 21.19 1 38 0 1
#> 199.1 19.81 1 NA 0 1
#> 6.1 15.64 1 39 0 0
#> 15.1 22.68 1 48 0 0
#> 8.1 18.43 1 32 0 0
#> 66 22.13 1 53 0 0
#> 88.1 18.37 1 47 0 0
#> 188.1 16.16 1 46 0 1
#> 106 16.67 1 49 1 0
#> 125.1 15.65 1 67 1 0
#> 85 16.44 1 36 0 0
#> 108 18.29 1 39 0 1
#> 159.1 10.55 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 154.2 12.63 1 20 1 0
#> 41.1 18.02 1 40 1 0
#> 123 13.00 1 44 1 0
#> 137 24.00 0 45 1 0
#> 94 24.00 0 51 0 1
#> 176 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 186 24.00 0 45 1 0
#> 198 24.00 0 66 0 1
#> 172 24.00 0 41 0 0
#> 173 24.00 0 19 0 1
#> 46 24.00 0 71 0 0
#> 31 24.00 0 36 0 1
#> 17 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 20 24.00 0 46 1 0
#> 191 24.00 0 60 0 1
#> 12 24.00 0 63 0 0
#> 9 24.00 0 31 1 0
#> 94.1 24.00 0 51 0 1
#> 122 24.00 0 66 0 0
#> 102 24.00 0 49 0 0
#> 47 24.00 0 38 0 1
#> 62 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 38 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 75 24.00 0 21 1 0
#> 98 24.00 0 34 1 0
#> 137.1 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 20.1 24.00 0 46 1 0
#> 161 24.00 0 45 0 0
#> 27 24.00 0 63 1 0
#> 196 24.00 0 19 0 0
#> 94.2 24.00 0 51 0 1
#> 75.1 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 196.1 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 137.2 24.00 0 45 1 0
#> 143 24.00 0 51 0 0
#> 46.1 24.00 0 71 0 0
#> 118 24.00 0 44 1 0
#> 9.1 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 11 24.00 0 42 0 1
#> 46.2 24.00 0 71 0 0
#> 46.3 24.00 0 71 0 0
#> 165 24.00 0 47 0 0
#> 102.1 24.00 0 49 0 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 132 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 141.1 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 174 24.00 0 49 1 0
#> 151 24.00 0 42 0 0
#> 200 24.00 0 64 0 0
#> 119 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 2 24.00 0 9 0 0
#> 87 24.00 0 27 0 0
#> 182 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 151.1 24.00 0 42 0 0
#> 112.1 24.00 0 61 0 0
#> 118.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 17.1 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 176.1 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 200.1 24.00 0 64 0 0
#> 54.1 24.00 0 53 1 0
#> 148 24.00 0 61 1 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 122.1 24.00 0 66 0 0
#> 196.2 24.00 0 19 0 0
#> 98.1 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 46.4 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.329 NA NA NA
#> 2 age, Cure model 0.00345 NA NA NA
#> 3 grade_ii, Cure model 0.248 NA NA NA
#> 4 grade_iii, Cure model 0.848 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0100 NA NA NA
#> 2 grade_ii, Survival model 0.751 NA NA NA
#> 3 grade_iii, Survival model 0.323 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.32935 0.00345 0.24823 0.84815
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 252.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.329348164 0.003450279 0.248231679 0.848154915
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0100266 0.7512950 0.3226116
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.643681235 0.203059035 0.914640988 0.903856514 0.666089617 0.871255030
#> [7] 0.479893577 0.806594095 0.946998566 0.806594095 0.176091296 0.024702192
#> [13] 0.017366152 0.666089617 0.143411329 0.512170632 0.849626228 0.289107900
#> [19] 0.893015945 0.752902011 0.125888789 0.038627009 0.212264540 0.968305848
#> [25] 0.544617334 0.194010278 0.632542747 0.091031816 0.038627009 0.763628291
#> [31] 0.946998566 0.415027889 0.074639035 0.501369664 0.393724115 0.361483917
#> [37] 0.654857737 0.309261164 0.240424331 0.806594095 0.052879831 0.577301735
#> [43] 0.610355232 0.838787573 0.599262614 0.108041096 0.240424331 0.259617292
#> [49] 0.059995027 0.289107900 0.329781809 0.989377883 0.184973363 0.925414950
#> [55] 0.555608007 0.763628291 0.721248439 0.361483917 0.279093774 0.621405880
#> [61] 0.091031816 0.143411329 0.447092718 0.001497398 0.721248439 0.710176818
#> [67] 0.259617292 0.031555815 0.785202268 0.436355210 0.116985619 0.785202268
#> [73] 0.425654085 0.006977883 0.925414950 0.688035199 0.212264540 0.230880370
#> [79] 0.533660989 0.457971987 0.134712952 0.143411329 0.006977883 0.361483917
#> [85] 0.882142512 0.143411329 0.577301735 0.059995027 0.309261164 0.082667801
#> [91] 0.329781809 0.512170632 0.468970806 0.555608007 0.479893577 0.350794049
#> [97] 0.849626228 0.968305848 0.721248439 0.393724115 0.699137876 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 13 150 183 187 60 61 192 43 70 43.1 90 129 164
#> 14.34 20.33 9.24 9.92 13.15 10.12 16.44 12.10 7.38 12.10 20.94 23.41 23.60
#> 60.1 36 188 159 179 101 42 139 113 166 25 26 128
#> 13.15 21.19 16.16 10.55 18.63 9.97 12.43 21.49 22.86 19.98 6.32 15.77 20.35
#> 96 175 113.1 56 70.1 40 169 79 41 51 81 8 58
#> 14.54 21.91 22.86 12.21 7.38 18.00 22.41 16.23 18.02 18.23 14.06 18.43 19.34
#> 43.2 63 6 167 107 39 136 58.1 76 15 179.1 88 127
#> 12.10 22.77 15.64 15.55 11.18 15.59 21.83 19.34 19.22 22.68 18.63 18.37 3.53
#> 68 16 125 56.1 154 51.1 97 133 175.1 36.1 30 78 154.1
#> 20.62 8.71 15.65 12.21 12.63 18.23 19.14 14.65 21.91 21.19 17.43 23.88 12.63
#> 14 76.1 92 49 111 197 49.1 110 86 16.1 155 166.1 170
#> 12.89 19.22 22.92 12.19 17.45 21.60 12.19 17.56 23.81 8.71 13.08 19.98 19.54
#> 100 23 153 36.2 86.1 51.2 145 99 6.1 15.1 8.1 66 88.1
#> 16.07 16.92 21.33 21.19 23.81 18.23 10.07 21.19 15.64 22.68 18.43 22.13 18.37
#> 188.1 106 125.1 85 108 159.1 25.1 154.2 41.1 123 137 94 176
#> 16.16 16.67 15.65 16.44 18.29 10.55 6.32 12.63 18.02 13.00 24.00 24.00 24.00
#> 53 186 198 172 173 46 31 17 141 65 20 191 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 94.1 122 102 47 62 64 38 19 75 98 137.1 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.1 161 27 196 94.2 75.1 1 196.1 121 137.2 143 46.1 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.1 95 11 46.2 46.3 165 102.1 54 109 121.1 112 132 80
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141.1 62.1 7 174 151 200 119 193 116 2 87 182 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 118.1 82 17.1 83 176.1 131 33 109.1 200.1 54.1 148 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122.1 196.2 98.1 160 46.4
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[42]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003369968 0.429957521 0.429453671
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.542792668 0.008379259 0.372007999
#> grade_iii, Cure model
#> 0.910825637
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 86 23.81 1 58 0 1
#> 18 15.21 1 49 1 0
#> 85 16.44 1 36 0 0
#> 5 16.43 1 51 0 1
#> 167 15.55 1 56 1 0
#> 23 16.92 1 61 0 0
#> 105 19.75 1 60 0 0
#> 39 15.59 1 37 0 1
#> 36 21.19 1 48 0 1
#> 49 12.19 1 48 1 0
#> 197.1 21.60 1 69 1 0
#> 13 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 93 10.33 1 52 0 1
#> 76 19.22 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 190 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 6.1 15.64 1 39 0 0
#> 70 7.38 1 30 1 0
#> 63 22.77 1 31 1 0
#> 89 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 153 21.33 1 55 1 0
#> 23.1 16.92 1 61 0 0
#> 60 13.15 1 38 1 0
#> 125 15.65 1 67 1 0
#> 39.1 15.59 1 37 0 1
#> 70.1 7.38 1 30 1 0
#> 30 17.43 1 78 0 0
#> 183 9.24 1 67 1 0
#> 192 16.44 1 31 1 0
#> 6.2 15.64 1 39 0 0
#> 150 20.33 1 48 0 0
#> 58 19.34 1 39 0 0
#> 39.2 15.59 1 37 0 1
#> 78 23.88 1 43 0 0
#> 189 10.51 1 NA 1 0
#> 63.1 22.77 1 31 1 0
#> 154 12.63 1 20 1 0
#> 167.1 15.55 1 56 1 0
#> 197.2 21.60 1 69 1 0
#> 81 14.06 1 34 0 0
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 107 11.18 1 54 1 0
#> 92 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 188 16.16 1 46 0 1
#> 171 16.57 1 41 0 1
#> 167.2 15.55 1 56 1 0
#> 183.1 9.24 1 67 1 0
#> 168 23.72 1 70 0 0
#> 50 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 181 16.46 1 45 0 1
#> 78.1 23.88 1 43 0 0
#> 101 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 15.1 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 190.1 20.81 1 42 1 0
#> 57.1 14.46 1 45 0 1
#> 68 20.62 1 44 0 0
#> 175 21.91 1 43 0 0
#> 14 12.89 1 21 0 0
#> 139 21.49 1 63 1 0
#> 30.1 17.43 1 78 0 0
#> 58.1 19.34 1 39 0 0
#> 111 17.45 1 47 0 1
#> 129 23.41 1 53 1 0
#> 128 20.35 1 35 0 1
#> 158 20.14 1 74 1 0
#> 181.1 16.46 1 45 0 1
#> 167.3 15.55 1 56 1 0
#> 93.1 10.33 1 52 0 1
#> 183.2 9.24 1 67 1 0
#> 59 10.16 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 63.2 22.77 1 31 1 0
#> 189.1 10.51 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 180.1 14.82 1 37 0 0
#> 134 17.81 1 47 1 0
#> 88 18.37 1 47 0 0
#> 194 22.40 1 38 0 1
#> 10 10.53 1 34 0 0
#> 30.2 17.43 1 78 0 0
#> 42 12.43 1 49 0 1
#> 39.3 15.59 1 37 0 1
#> 30.3 17.43 1 78 0 0
#> 51 18.23 1 83 0 1
#> 106.1 16.67 1 49 1 0
#> 41 18.02 1 40 1 0
#> 85.1 16.44 1 36 0 0
#> 6.3 15.64 1 39 0 0
#> 55 19.34 1 69 0 1
#> 195 11.76 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 175.1 21.91 1 43 0 0
#> 179.1 18.63 1 42 0 0
#> 100 16.07 1 60 0 0
#> 145.1 10.07 1 65 1 0
#> 25 6.32 1 34 1 0
#> 113 22.86 1 34 0 0
#> 51.1 18.23 1 83 0 1
#> 113.1 22.86 1 34 0 0
#> 190.2 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 137 24.00 0 45 1 0
#> 118 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 160 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 178 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 11 24.00 0 42 0 1
#> 200 24.00 0 64 0 0
#> 64.1 24.00 0 43 0 0
#> 186 24.00 0 45 1 0
#> 162.1 24.00 0 51 0 0
#> 3 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 137.1 24.00 0 45 1 0
#> 156 24.00 0 50 1 0
#> 48 24.00 0 31 1 0
#> 71 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 27 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 132.1 24.00 0 55 0 0
#> 176 24.00 0 43 0 1
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 120.1 24.00 0 68 0 1
#> 22 24.00 0 52 1 0
#> 54 24.00 0 53 1 0
#> 173.1 24.00 0 19 0 1
#> 119 24.00 0 17 0 0
#> 21.1 24.00 0 47 0 0
#> 137.2 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 82 24.00 0 34 0 0
#> 102 24.00 0 49 0 0
#> 83 24.00 0 6 0 0
#> 33 24.00 0 53 0 0
#> 22.1 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 165 24.00 0 47 0 0
#> 34.1 24.00 0 36 0 0
#> 148 24.00 0 61 1 0
#> 103 24.00 0 56 1 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 109.1 24.00 0 48 0 0
#> 21.2 24.00 0 47 0 0
#> 172 24.00 0 41 0 0
#> 126.2 24.00 0 48 0 0
#> 172.1 24.00 0 41 0 0
#> 31 24.00 0 36 0 1
#> 21.3 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 94 24.00 0 51 0 1
#> 122 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 186.1 24.00 0 45 1 0
#> 126.3 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 198 24.00 0 66 0 1
#> 172.2 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 27.1 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 118.1 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 173.2 24.00 0 19 0 1
#> 7 24.00 0 37 1 0
#> 173.3 24.00 0 19 0 1
#> 182 24.00 0 35 0 0
#> 148.1 24.00 0 61 1 0
#> 7.1 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.543 NA NA NA
#> 2 age, Cure model 0.00838 NA NA NA
#> 3 grade_ii, Cure model 0.372 NA NA NA
#> 4 grade_iii, Cure model 0.911 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00337 NA NA NA
#> 2 grade_ii, Survival model 0.430 NA NA NA
#> 3 grade_iii, Survival model 0.429 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.542793 0.008379 0.372008 0.910826
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 260.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.542792668 0.008379259 0.372007999 0.910825637
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003369968 0.429957521 0.429453671
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.20996855 0.04274088 0.75301462 0.57660682 0.61215808 0.71861023
#> [7] 0.51190409 0.33535224 0.68375092 0.25966479 0.86564633 0.20996855
#> [13] 0.80519013 0.76173640 0.89134140 0.39137893 0.33535224 0.26959238
#> [19] 0.64824722 0.06856224 0.64824722 0.95854566 0.12805627 0.78789271
#> [25] 0.24961938 0.51190409 0.82253890 0.63924508 0.68375092 0.95854566
#> [31] 0.47542192 0.93360731 0.57660682 0.64824722 0.31636945 0.36367700
#> [37] 0.68375092 0.01986330 0.12805627 0.83983952 0.71861023 0.20996855
#> [43] 0.81385951 0.97513167 0.00637417 0.87422411 0.09356777 0.15774569
#> [49] 0.99173077 0.62120682 0.54911519 0.71861023 0.93360731 0.05532976
#> [55] 0.53060850 0.55839451 0.01986330 0.92516788 0.85704233 0.15774569
#> [61] 0.40077600 0.26959238 0.78789271 0.29730905 0.18916735 0.83118614
#> [67] 0.23946075 0.47542192 0.36367700 0.46619545 0.08133701 0.30689331
#> [73] 0.32588819 0.55839451 0.71861023 0.89134140 0.93360731 0.77047284
#> [79] 0.12805627 0.57660682 0.77047284 0.45691179 0.41946424 0.17862602
#> [85] 0.88277826 0.47542192 0.84845412 0.68375092 0.47542192 0.42894612
#> [91] 0.53060850 0.44756890 0.57660682 0.64824722 0.36367700 0.90829161
#> [97] 0.18916735 0.40077600 0.63021414 0.90829161 0.98344421 0.10532289
#> [103] 0.42894612 0.10532289 0.26959238 0.35420554 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 197 86 18 85 5 167 23 105 39 36 49 197.1 13
#> 21.60 23.81 15.21 16.44 16.43 15.55 16.92 19.75 15.59 21.19 12.19 21.60 14.34
#> 157 93 76 105.1 190 6 164 6.1 70 63 57 153 23.1
#> 15.10 10.33 19.22 19.75 20.81 15.64 23.60 15.64 7.38 22.77 14.46 21.33 16.92
#> 60 125 39.1 70.1 30 183 192 6.2 150 58 39.2 78 63.1
#> 13.15 15.65 15.59 7.38 17.43 9.24 16.44 15.64 20.33 19.34 15.59 23.88 22.77
#> 154 167.1 197.2 81 77 24 107 92 15 91 188 171 167.2
#> 12.63 15.55 21.60 14.06 7.27 23.89 11.18 22.92 22.68 5.33 16.16 16.57 15.55
#> 183.1 168 106 181 78.1 101 56 15.1 179 190.1 57.1 68 175
#> 9.24 23.72 16.67 16.46 23.88 9.97 12.21 22.68 18.63 20.81 14.46 20.62 21.91
#> 14 139 30.1 58.1 111 129 128 158 181.1 167.3 93.1 183.2 180
#> 12.89 21.49 17.43 19.34 17.45 23.41 20.35 20.14 16.46 15.55 10.33 9.24 14.82
#> 63.2 192.1 180.1 134 88 194 10 30.2 42 39.3 30.3 51 106.1
#> 22.77 16.44 14.82 17.81 18.37 22.40 10.53 17.43 12.43 15.59 17.43 18.23 16.67
#> 41 85.1 6.3 55 145 175.1 179.1 100 145.1 25 113 51.1 113.1
#> 18.02 16.44 15.64 19.34 10.07 21.91 18.63 16.07 10.07 6.32 22.86 18.23 22.86
#> 190.2 170 137 118 19 34 160 162 126 161 178 64 11
#> 20.81 19.54 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 64.1 186 162.1 3 21 137.1 156 48 71 2 109 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 143 146 27 62 112 132.1 176 173 147 120.1 22 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 119 21.1 137.2 163 131 82 102 83 33 22.1 126.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 148 103 74 185 46 38 109.1 21.2 172 126.2 172.1 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21.3 151 94 122 71.1 28 65 44 186.1 126.3 20 198 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 27.1 35 142 118.1 112.1 173.2 7 173.3 182 148.1 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[43]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.002424571 0.350683054 -0.007738248
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.486666977 0.007158579 0.426421780
#> grade_iii, Cure model
#> 0.767510173
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 106 16.67 1 49 1 0
#> 117 17.46 1 26 0 1
#> 150 20.33 1 48 0 0
#> 177 12.53 1 75 0 0
#> 37 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 93 10.33 1 52 0 1
#> 192 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 55 19.34 1 69 0 1
#> 179 18.63 1 42 0 0
#> 50 10.02 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 76 19.22 1 54 0 1
#> 108 18.29 1 39 0 1
#> 10 10.53 1 34 0 0
#> 190 20.81 1 42 1 0
#> 86 23.81 1 58 0 1
#> 100 16.07 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 190.1 20.81 1 42 1 0
#> 184 17.77 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 23 16.92 1 61 0 0
#> 4 17.64 1 NA 0 1
#> 100.1 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 180 14.82 1 37 0 0
#> 90 20.94 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 171 16.57 1 41 0 1
#> 155 13.08 1 26 0 0
#> 171.1 16.57 1 41 0 1
#> 8.1 18.43 1 32 0 0
#> 90.1 20.94 1 50 0 1
#> 136 21.83 1 43 0 1
#> 123 13.00 1 44 1 0
#> 100.2 16.07 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 99 21.19 1 38 0 1
#> 79 16.23 1 54 1 0
#> 55.1 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 114 13.68 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 195.1 11.76 1 NA 1 0
#> 14 12.89 1 21 0 0
#> 14.1 12.89 1 21 0 0
#> 134 17.81 1 47 1 0
#> 199 19.81 1 NA 0 1
#> 177.2 12.53 1 75 0 0
#> 37.1 12.52 1 57 1 0
#> 123.1 13.00 1 44 1 0
#> 192.1 16.44 1 31 1 0
#> 41 18.02 1 40 1 0
#> 63 22.77 1 31 1 0
#> 107 11.18 1 54 1 0
#> 52.1 10.42 1 52 0 1
#> 70 7.38 1 30 1 0
#> 150.1 20.33 1 48 0 0
#> 177.3 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 16 8.71 1 71 0 1
#> 133.1 14.65 1 57 0 0
#> 150.2 20.33 1 48 0 0
#> 24 23.89 1 38 0 0
#> 195.2 11.76 1 NA 1 0
#> 14.2 12.89 1 21 0 0
#> 15 22.68 1 48 0 0
#> 108.2 18.29 1 39 0 1
#> 110.1 17.56 1 65 0 1
#> 4.1 17.64 1 NA 0 1
#> 136.1 21.83 1 43 0 1
#> 10.1 10.53 1 34 0 0
#> 25 6.32 1 34 1 0
#> 158 20.14 1 74 1 0
#> 61 10.12 1 36 0 1
#> 179.1 18.63 1 42 0 0
#> 13 14.34 1 54 0 1
#> 23.1 16.92 1 61 0 0
#> 99.1 21.19 1 38 0 1
#> 68 20.62 1 44 0 0
#> 88 18.37 1 47 0 0
#> 117.1 17.46 1 26 0 1
#> 41.1 18.02 1 40 1 0
#> 41.2 18.02 1 40 1 0
#> 93.1 10.33 1 52 0 1
#> 154.1 12.63 1 20 1 0
#> 18 15.21 1 49 1 0
#> 91 5.33 1 61 0 1
#> 81 14.06 1 34 0 0
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 66 22.13 1 53 0 0
#> 134.1 17.81 1 47 1 0
#> 114.1 13.68 1 NA 0 0
#> 155.1 13.08 1 26 0 0
#> 107.1 11.18 1 54 1 0
#> 105 19.75 1 60 0 0
#> 40 18.00 1 28 1 0
#> 108.3 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 106.1 16.67 1 49 1 0
#> 5 16.43 1 51 0 1
#> 57 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 68.1 20.62 1 44 0 0
#> 134.2 17.81 1 47 1 0
#> 83 24.00 0 6 0 0
#> 193 24.00 0 45 0 1
#> 126 24.00 0 48 0 0
#> 182 24.00 0 35 0 0
#> 84 24.00 0 39 0 1
#> 75 24.00 0 21 1 0
#> 142 24.00 0 53 0 0
#> 75.1 24.00 0 21 1 0
#> 178 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 148 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 126.1 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 62 24.00 0 71 0 0
#> 84.1 24.00 0 39 0 1
#> 44 24.00 0 56 0 0
#> 119 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 118 24.00 0 44 1 0
#> 138 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 120 24.00 0 68 0 1
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 54 24.00 0 53 1 0
#> 115 24.00 0 NA 1 0
#> 44.1 24.00 0 56 0 0
#> 143 24.00 0 51 0 0
#> 7 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 83.1 24.00 0 6 0 0
#> 162 24.00 0 51 0 0
#> 135 24.00 0 58 1 0
#> 82.1 24.00 0 34 0 0
#> 67 24.00 0 25 0 0
#> 165.1 24.00 0 47 0 0
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 200 24.00 0 64 0 0
#> 104.1 24.00 0 50 1 0
#> 102 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 122 24.00 0 66 0 0
#> 104.2 24.00 0 50 1 0
#> 121 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 132 24.00 0 55 0 0
#> 121.1 24.00 0 57 1 0
#> 142.1 24.00 0 53 0 0
#> 2 24.00 0 9 0 0
#> 11.1 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 35 24.00 0 51 0 0
#> 33 24.00 0 53 0 0
#> 132.1 24.00 0 55 0 0
#> 162.1 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 147 24.00 0 76 1 0
#> 120.1 24.00 0 68 0 1
#> 112 24.00 0 61 0 0
#> 182.1 24.00 0 35 0 0
#> 67.1 24.00 0 25 0 0
#> 182.2 24.00 0 35 0 0
#> 193.1 24.00 0 45 0 1
#> 11.2 24.00 0 42 0 1
#> 82.2 24.00 0 34 0 0
#> 173 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 193.2 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 54.1 24.00 0 53 1 0
#> 72 24.00 0 40 0 1
#> 83.2 24.00 0 6 0 0
#> 182.3 24.00 0 35 0 0
#> 144 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 102.1 24.00 0 49 0 0
#> 148.1 24.00 0 61 1 0
#> 7.1 24.00 0 37 1 0
#> 120.2 24.00 0 68 0 1
#> 182.4 24.00 0 35 0 0
#> 115.2 24.00 0 NA 1 0
#> 142.2 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 2.1 24.00 0 9 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.487 NA NA NA
#> 2 age, Cure model 0.00716 NA NA NA
#> 3 grade_ii, Cure model 0.426 NA NA NA
#> 4 grade_iii, Cure model 0.768 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00242 NA NA NA
#> 2 grade_ii, Survival model 0.351 NA NA NA
#> 3 grade_iii, Survival model -0.00774 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.486667 0.007159 0.426422 0.767510
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 256.5
#> Residual Deviance: 250.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.486666977 0.007158579 0.426421780 0.767510173
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.002424571 0.350683054 -0.007738248
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.60121539 0.56487668 0.28883038 0.83234314 0.86480787 0.71463838
#> [7] 0.93679436 0.63677193 0.46193943 0.34129085 0.37214441 0.97641000
#> [13] 0.39245315 0.36178630 0.42288646 0.90502043 0.24541976 0.04798055
#> [19] 0.67177960 0.24541976 0.53737713 0.83234314 0.58309113 0.67177960
#> [25] 0.92092460 0.88100204 0.70604858 0.21007199 0.42288646 0.61901815
#> [31] 0.75726267 0.61901815 0.39245315 0.21007199 0.13688933 0.77419438
#> [37] 0.67177960 0.54662883 0.17526172 0.66305897 0.34129085 0.81581961
#> [43] 0.23365288 0.79091406 0.79091406 0.51005255 0.83234314 0.86480787
#> [49] 0.77419438 0.63677193 0.47198160 0.08061000 0.88909221 0.92092460
#> [55] 0.96851013 0.28883038 0.83234314 0.12313399 0.96057613 0.71463838
#> [61] 0.28883038 0.01225072 0.79091406 0.09504024 0.42288646 0.54662883
#> [67] 0.13688933 0.90502043 0.98429920 0.32020402 0.95263041 0.37214441
#> [73] 0.74020196 0.58309113 0.17526172 0.26722377 0.41267771 0.56487668
#> [79] 0.47198160 0.47198160 0.93679436 0.81581961 0.69744896 0.99215427
#> [85] 0.74873649 0.03049516 0.10920956 0.51005255 0.75726267 0.88909221
#> [91] 0.33077373 0.50046753 0.42288646 0.16253804 0.60121539 0.65426680
#> [97] 0.73165451 0.06467892 0.17526172 0.26722377 0.51005255 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 106 117 150 177 37 133 93 192 51 55 179 77 8
#> 16.67 17.46 20.33 12.53 12.52 14.65 10.33 16.44 18.23 19.34 18.63 7.27 18.43
#> 76 108 10 190 86 100 190.1 184 177.1 23 100.1 52 49
#> 19.22 18.29 10.53 20.81 23.81 16.07 20.81 17.77 12.53 16.92 16.07 10.42 12.19
#> 180 90 108.1 171 155 171.1 8.1 90.1 136 123 100.2 110 99
#> 14.82 20.94 18.29 16.57 13.08 16.57 18.43 20.94 21.83 13.00 16.07 17.56 21.19
#> 79 55.1 154 32 14 14.1 134 177.2 37.1 123.1 192.1 41 63
#> 16.23 19.34 12.63 20.90 12.89 12.89 17.81 12.53 12.52 13.00 16.44 18.02 22.77
#> 107 52.1 70 150.1 177.3 175 16 133.1 150.2 24 14.2 15 108.2
#> 11.18 10.42 7.38 20.33 12.53 21.91 8.71 14.65 20.33 23.89 12.89 22.68 18.29
#> 110.1 136.1 10.1 25 158 61 179.1 13 23.1 99.1 68 88 117.1
#> 17.56 21.83 10.53 6.32 20.14 10.12 18.63 14.34 16.92 21.19 20.62 18.37 17.46
#> 41.1 41.2 93.1 154.1 18 91 81 78 66 134.1 155.1 107.1 105
#> 18.02 18.02 10.33 12.63 15.21 5.33 14.06 23.88 22.13 17.81 13.08 11.18 19.75
#> 40 108.3 153 106.1 5 57 164 36 68.1 134.2 83 193 126
#> 18.00 18.29 21.33 16.67 16.43 14.46 23.60 21.19 20.62 17.81 24.00 24.00 24.00
#> 182 84 75 142 75.1 178 109 148 19 126.1 34 62 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 119 104 118 138 98 174 120 82 165 54 44.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 95 83.1 162 135 82.1 67 165.1 71 17 200 104.1 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 122 104.2 121 11 132 121.1 142.1 2 11.1 87 35 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132.1 162.1 147 120.1 112 182.1 67.1 182.2 193.1 11.2 82.2 173 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.2 141 27 54.1 72 83.2 182.3 144 80 102.1 148.1 7.1 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.4 142.2 109.1 2.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[44]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0001523465 0.3111930993 0.4143590893
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.03216429 0.01932654 0.19373481
#> grade_iii, Cure model
#> 0.73587677
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 55 19.34 1 69 0 1
#> 93 10.33 1 52 0 1
#> 105 19.75 1 60 0 0
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 52 10.42 1 52 0 1
#> 181 16.46 1 45 0 1
#> 39 15.59 1 37 0 1
#> 66 22.13 1 53 0 0
#> 42 12.43 1 49 0 1
#> 78 23.88 1 43 0 0
#> 150 20.33 1 48 0 0
#> 181.1 16.46 1 45 0 1
#> 183 9.24 1 67 1 0
#> 96 14.54 1 33 0 1
#> 197 21.60 1 69 1 0
#> 139 21.49 1 63 1 0
#> 123 13.00 1 44 1 0
#> 39.1 15.59 1 37 0 1
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 43.1 12.10 1 61 0 1
#> 96.1 14.54 1 33 0 1
#> 4 17.64 1 NA 0 1
#> 50 10.02 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 66.1 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 57.1 14.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 25 6.32 1 34 1 0
#> 164 23.60 1 76 0 1
#> 130 16.47 1 53 0 1
#> 158 20.14 1 74 1 0
#> 92 22.92 1 47 0 1
#> 140 12.68 1 59 1 0
#> 149.1 8.37 1 33 1 0
#> 63.1 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 23.1 16.92 1 61 0 0
#> 106.1 16.67 1 49 1 0
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 123.1 13.00 1 44 1 0
#> 42.1 12.43 1 49 0 1
#> 32 20.90 1 37 1 0
#> 158.1 20.14 1 74 1 0
#> 15 22.68 1 48 0 0
#> 100 16.07 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 60 13.15 1 38 1 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 41 18.02 1 40 1 0
#> 43.2 12.10 1 61 0 1
#> 110 17.56 1 65 0 1
#> 88 18.37 1 47 0 0
#> 6 15.64 1 39 0 0
#> 170.1 19.54 1 43 0 1
#> 123.2 13.00 1 44 1 0
#> 105.1 19.75 1 60 0 0
#> 18 15.21 1 49 1 0
#> 39.2 15.59 1 37 0 1
#> 45 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 16 8.71 1 71 0 1
#> 179 18.63 1 42 0 0
#> 52.1 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 157 15.10 1 47 0 0
#> 177.1 12.53 1 75 0 0
#> 6.1 15.64 1 39 0 0
#> 36 21.19 1 48 0 1
#> 13 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 23.2 16.92 1 61 0 0
#> 113 22.86 1 34 0 0
#> 93.1 10.33 1 52 0 1
#> 134 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 32.1 20.90 1 37 1 0
#> 76 19.22 1 54 0 1
#> 134.1 17.81 1 47 1 0
#> 76.1 19.22 1 54 0 1
#> 78.1 23.88 1 43 0 0
#> 183.1 9.24 1 67 1 0
#> 23.3 16.92 1 61 0 0
#> 190.1 20.81 1 42 1 0
#> 97.2 19.14 1 65 0 1
#> 183.2 9.24 1 67 1 0
#> 8 18.43 1 32 0 0
#> 134.2 17.81 1 47 1 0
#> 154 12.63 1 20 1 0
#> 154.1 12.63 1 20 1 0
#> 145 10.07 1 65 1 0
#> 130.1 16.47 1 53 0 1
#> 124 9.73 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 89 11.44 1 NA 0 0
#> 105.2 19.75 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 180.1 14.82 1 37 0 0
#> 45.1 17.42 1 54 0 1
#> 158.2 20.14 1 74 1 0
#> 129 23.41 1 53 1 0
#> 49 12.19 1 48 1 0
#> 159 10.55 1 50 0 1
#> 11 24.00 0 42 0 1
#> 28 24.00 0 67 1 0
#> 47 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 2 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 165 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 173 24.00 0 19 0 1
#> 176 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 35 24.00 0 51 0 0
#> 109 24.00 0 48 0 0
#> 172 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 102 24.00 0 49 0 0
#> 83 24.00 0 6 0 0
#> 191 24.00 0 60 0 1
#> 118 24.00 0 44 1 0
#> 160 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 104 24.00 0 50 1 0
#> 2.1 24.00 0 9 0 0
#> 62 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 48.1 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 191.1 24.00 0 60 0 1
#> 165.1 24.00 0 47 0 0
#> 176.1 24.00 0 43 0 1
#> 103.1 24.00 0 56 1 0
#> 163.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 176.2 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 75 24.00 0 21 1 0
#> 138.1 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 148 24.00 0 61 1 0
#> 1.1 24.00 0 23 1 0
#> 67 24.00 0 25 0 0
#> 21.1 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 71.1 24.00 0 51 0 0
#> 104.1 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 191.2 24.00 0 60 0 1
#> 48.2 24.00 0 31 1 0
#> 21.2 24.00 0 47 0 0
#> 141 24.00 0 44 1 0
#> 104.2 24.00 0 50 1 0
#> 7.1 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 151 24.00 0 42 0 0
#> 143 24.00 0 51 0 0
#> 71.2 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 28.1 24.00 0 67 1 0
#> 44.1 24.00 0 56 0 0
#> 64 24.00 0 43 0 0
#> 118.1 24.00 0 44 1 0
#> 163.2 24.00 0 66 0 0
#> 120.1 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 31 24.00 0 36 0 1
#> 1.2 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 64.1 24.00 0 43 0 0
#> 112 24.00 0 61 0 0
#> 178 24.00 0 52 1 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 44.2 24.00 0 56 0 0
#> 176.3 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 11.1 24.00 0 42 0 1
#> 118.2 24.00 0 44 1 0
#> 144.1 24.00 0 28 0 1
#> 87 24.00 0 27 0 0
#> 62.1 24.00 0 71 0 0
#> 137.1 24.00 0 45 1 0
#> 160.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.03 NA NA NA
#> 2 age, Cure model 0.0193 NA NA NA
#> 3 grade_ii, Cure model 0.194 NA NA NA
#> 4 grade_iii, Cure model 0.736 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000152 NA NA NA
#> 2 grade_ii, Survival model 0.311 NA NA NA
#> 3 grade_iii, Survival model 0.414 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03216 0.01933 0.19373 0.73588
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 256.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.03216429 0.01932654 0.19373481 0.73587677
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0001523465 0.3111930993 0.4143590893
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.39121722 0.92075828 0.34144791 0.71254371 0.75275303 0.27947249
#> [7] 0.72868274 0.90604326 0.62244488 0.67213545 0.17254150 0.85357827
#> [13] 0.02069785 0.30062627 0.62244488 0.94993626 0.73679665 0.21016000
#> [19] 0.22241919 0.79214045 0.67213545 0.23442825 0.87632611 0.87632611
#> [25] 0.73679665 0.13445795 0.17254150 0.58867306 0.75275303 0.97861970
#> [31] 0.99286881 0.05589642 0.60568267 0.31139329 0.10607925 0.81522862
#> [37] 0.97861970 0.13445795 0.55478332 0.55478332 0.58867306 0.94265404
#> [43] 0.63897397 0.79214045 0.85357827 0.25770389 0.31139329 0.15949572
#> [49] 0.64729207 0.77642292 0.42007840 0.42007840 0.37147999 0.48413177
#> [55] 0.87632611 0.51982291 0.46580478 0.65560918 0.37147999 0.79214045
#> [61] 0.34144791 0.69630950 0.67213545 0.53756181 0.83827606 0.97142994
#> [67] 0.44728777 0.90604326 0.19762361 0.70442694 0.83827606 0.65560918
#> [73] 0.24621023 0.76853421 0.55478332 0.12027197 0.92075828 0.49331813
#> [79] 0.09082132 0.25770389 0.40108015 0.49331813 0.40108015 0.02069785
#> [85] 0.94993626 0.55478332 0.27947249 0.42007840 0.94993626 0.45654673
#> [91] 0.49331813 0.82297065 0.82297065 0.93535077 0.60568267 0.78428184
#> [97] 0.34144791 0.46580478 0.52873099 0.71254371 0.53756181 0.31139329
#> [103] 0.07411767 0.86873789 0.89859179 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 55 93 105 180 57 190 133 52 181 39 66 42 78
#> 19.34 10.33 19.75 14.82 14.46 20.81 14.65 10.42 16.46 15.59 22.13 12.43 23.88
#> 150 181.1 183 96 197 139 123 39.1 153 43 43.1 96.1 63
#> 20.33 16.46 9.24 14.54 21.60 21.49 13.00 15.59 21.33 12.10 12.10 14.54 22.77
#> 66.1 106 57.1 149 25 164 130 158 92 140 149.1 63.1 23
#> 22.13 16.67 14.46 8.37 6.32 23.60 16.47 20.14 22.92 12.68 8.37 22.77 16.92
#> 23.1 106.1 187 85 123.1 42.1 32 158.1 15 100 60 97 97.1
#> 16.92 16.67 9.92 16.44 13.00 12.43 20.90 20.14 22.68 16.07 13.15 19.14 19.14
#> 170 41 43.2 110 88 6 170.1 123.2 105.1 18 39.2 45 177
#> 19.54 18.02 12.10 17.56 18.37 15.64 19.54 13.00 19.75 15.21 15.59 17.42 12.53
#> 16 179 52.1 136 157 177.1 6.1 36 13 23.2 113 93.1 134
#> 8.71 18.63 10.42 21.83 15.10 12.53 15.64 21.19 14.34 16.92 22.86 10.33 17.81
#> 69 32.1 76 134.1 76.1 78.1 183.1 23.3 190.1 97.2 183.2 8 134.2
#> 23.23 20.90 19.22 17.81 19.22 23.88 9.24 16.92 20.81 19.14 9.24 18.43 17.81
#> 154 154.1 145 130.1 155 105.2 88.1 117 180.1 45.1 158.2 129 49
#> 12.63 12.63 10.07 16.47 13.08 19.75 18.37 17.46 14.82 17.42 20.14 23.41 12.19
#> 159 11 28 47 80 2 48 165 103 173 176 71 21
#> 10.55 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 109 172 193 1 102 83 191 118 160 135 104 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 74 33 48.1 138 163 146 191.1 165.1 176.1 103.1 163.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.2 44 75 138.1 65 148 1.1 67 21.1 20 71.1 104.1 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.2 48.2 21.2 141 104.2 7.1 144 151 143 71.2 137 28.1 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 118.1 163.2 120.1 121 31 1.2 95 116 64.1 112 178 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44.2 176.3 54 11.1 118.2 144.1 87 62.1 137.1 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[45]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004401039 0.744437141 0.235522628
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.327934128 0.006337511 0.004974572
#> grade_iii, Cure model
#> 0.877462139
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 8 18.43 1 32 0 0
#> 190 20.81 1 42 1 0
#> 92 22.92 1 47 0 1
#> 6.1 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 59 10.16 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 81 14.06 1 34 0 0
#> 108 18.29 1 39 0 1
#> 145 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 149 8.37 1 33 1 0
#> 69.1 23.23 1 25 0 1
#> 187 9.92 1 39 1 0
#> 136 21.83 1 43 0 1
#> 63 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 113 22.86 1 34 0 0
#> 99 21.19 1 38 0 1
#> 26 15.77 1 49 0 1
#> 39 15.59 1 37 0 1
#> 168 23.72 1 70 0 0
#> 60 13.15 1 38 1 0
#> 51 18.23 1 83 0 1
#> 25 6.32 1 34 1 0
#> 56 12.21 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 167 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 24 23.89 1 38 0 0
#> 197 21.60 1 69 1 0
#> 157 15.10 1 47 0 0
#> 123 13.00 1 44 1 0
#> 26.1 15.77 1 49 0 1
#> 70 7.38 1 30 1 0
#> 145.1 10.07 1 65 1 0
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 133 14.65 1 57 0 0
#> 5 16.43 1 51 0 1
#> 134 17.81 1 47 1 0
#> 66 22.13 1 53 0 0
#> 96 14.54 1 33 0 1
#> 61 10.12 1 36 0 1
#> 76 19.22 1 54 0 1
#> 30 17.43 1 78 0 0
#> 192 16.44 1 31 1 0
#> 79 16.23 1 54 1 0
#> 199 19.81 1 NA 0 1
#> 164 23.60 1 76 0 1
#> 199.1 19.81 1 NA 0 1
#> 55 19.34 1 69 0 1
#> 49 12.19 1 48 1 0
#> 45 17.42 1 54 0 1
#> 63.1 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 92.1 22.92 1 47 0 1
#> 99.1 21.19 1 38 0 1
#> 123.1 13.00 1 44 1 0
#> 113.1 22.86 1 34 0 0
#> 78 23.88 1 43 0 0
#> 55.1 19.34 1 69 0 1
#> 190.1 20.81 1 42 1 0
#> 128 20.35 1 35 0 1
#> 10 10.53 1 34 0 0
#> 149.1 8.37 1 33 1 0
#> 140 12.68 1 59 1 0
#> 49.1 12.19 1 48 1 0
#> 99.2 21.19 1 38 0 1
#> 184 17.77 1 38 0 0
#> 13 14.34 1 54 0 1
#> 108.1 18.29 1 39 0 1
#> 158 20.14 1 74 1 0
#> 153 21.33 1 55 1 0
#> 56.1 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 107 11.18 1 54 1 0
#> 158.1 20.14 1 74 1 0
#> 168.1 23.72 1 70 0 0
#> 113.2 22.86 1 34 0 0
#> 130.1 16.47 1 53 0 1
#> 155 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 63.2 22.77 1 31 1 0
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 140.1 12.68 1 59 1 0
#> 101.1 9.97 1 10 0 1
#> 181 16.46 1 45 0 1
#> 29 15.45 1 68 1 0
#> 149.2 8.37 1 33 1 0
#> 105 19.75 1 60 0 0
#> 99.3 21.19 1 38 0 1
#> 40 18.00 1 28 1 0
#> 128.1 20.35 1 35 0 1
#> 183 9.24 1 67 1 0
#> 59.1 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 187.1 9.92 1 39 1 0
#> 114 13.68 1 NA 0 0
#> 111 17.45 1 47 0 1
#> 36.1 21.19 1 48 0 1
#> 179 18.63 1 42 0 0
#> 195 11.76 1 NA 1 0
#> 100 16.07 1 60 0 0
#> 139.1 21.49 1 63 1 0
#> 49.2 12.19 1 48 1 0
#> 16 8.71 1 71 0 1
#> 152 24.00 0 36 0 1
#> 31 24.00 0 36 0 1
#> 65 24.00 0 57 1 0
#> 112 24.00 0 61 0 0
#> 73 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 9 24.00 0 31 1 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 135.1 24.00 0 58 1 0
#> 143 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 34 24.00 0 36 0 0
#> 34.1 24.00 0 36 0 0
#> 74 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 7 24.00 0 37 1 0
#> 48 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 185 24.00 0 44 1 0
#> 83 24.00 0 6 0 0
#> 3.1 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 163 24.00 0 66 0 0
#> 83.1 24.00 0 6 0 0
#> 17.1 24.00 0 38 0 1
#> 9.1 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 21 24.00 0 47 0 0
#> 163.1 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 48.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 53 24.00 0 32 0 1
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 141 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 118 24.00 0 44 1 0
#> 38.1 24.00 0 31 1 0
#> 74.1 24.00 0 43 0 1
#> 54.1 24.00 0 53 1 0
#> 64 24.00 0 43 0 0
#> 98.1 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 48.2 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 121.1 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 143.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 162 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 1.1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 27 24.00 0 63 1 0
#> 94 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 75 24.00 0 21 1 0
#> 172 24.00 0 41 0 0
#> 115.1 24.00 0 NA 1 0
#> 28 24.00 0 67 1 0
#> 73.1 24.00 0 NA 0 1
#> 178 24.00 0 52 1 0
#> 147.1 24.00 0 76 1 0
#> 62.1 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#> 135.2 24.00 0 58 1 0
#> 176.1 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 119.1 24.00 0 17 0 0
#> 163.2 24.00 0 66 0 0
#> 185.1 24.00 0 44 1 0
#> 46.1 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.328 NA NA NA
#> 2 age, Cure model 0.00634 NA NA NA
#> 3 grade_ii, Cure model 0.00497 NA NA NA
#> 4 grade_iii, Cure model 0.877 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00440 NA NA NA
#> 2 grade_ii, Survival model 0.744 NA NA NA
#> 3 grade_iii, Survival model 0.236 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.327934 0.006338 0.004975 0.877462
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 251.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.327934128 0.006337511 0.004974572 0.877462139
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004401039 0.744437141 0.235522628
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.656666677 0.463093675 0.324079520 0.096694689 0.656666677 0.379680037
#> [7] 0.463093675 0.910760294 0.746824199 0.481848700 0.894064030 0.070451739
#> [13] 0.960197019 0.070451739 0.927392210 0.205256533 0.161442997 0.791191939
#> [19] 0.122777450 0.258907320 0.638616276 0.674795700 0.029127584 0.755837193
#> [25] 0.500555790 0.992074611 0.825935036 0.379680037 0.683912632 0.593131812
#> [31] 0.004914191 0.216780087 0.701925328 0.773708139 0.638616276 0.984097434
#> [37] 0.894064030 0.565501974 0.710920348 0.611303609 0.519335614 0.193702433
#> [43] 0.719940690 0.885584042 0.434898131 0.546974580 0.593131812 0.620456529
#> [49] 0.055034412 0.407359034 0.843282836 0.556238111 0.161442997 0.407359034
#> [55] 0.096694689 0.258907320 0.773708139 0.122777450 0.016025232 0.407359034
#> [61] 0.324079520 0.342833277 0.877097542 0.960197019 0.799991306 0.843282836
#> [67] 0.258907320 0.528533653 0.737826298 0.481848700 0.361500615 0.248636574
#> [73] 0.825935036 0.817257634 0.868622439 0.361500615 0.029127584 0.122777450
#> [79] 0.565501974 0.764767022 0.227974253 0.161442997 0.314124647 0.258907320
#> [85] 0.799991306 0.910760294 0.583876640 0.692951798 0.960197019 0.398026881
#> [91] 0.258907320 0.510020131 0.342833277 0.943796660 0.444279150 0.719940690
#> [97] 0.927392210 0.537756414 0.258907320 0.453669949 0.629521205 0.227974253
#> [103] 0.843282836 0.951994223 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 6 8 190 92 6.1 166 8.1 101 81 108 145 69 149
#> 15.64 18.43 20.81 22.92 15.64 19.98 18.43 9.97 14.06 18.29 10.07 23.23 8.37
#> 69.1 187 136 63 14 113 99 26 39 168 60 51 25
#> 23.23 9.92 21.83 22.77 12.89 22.86 21.19 15.77 15.59 23.72 13.15 18.23 6.32
#> 56 166.1 167 85 24 197 157 123 26.1 70 145.1 130 133
#> 12.21 19.98 15.55 16.44 23.89 21.60 15.10 13.00 15.77 7.38 10.07 16.47 14.65
#> 5 134 66 96 61 76 30 192 79 164 55 49 45
#> 16.43 17.81 22.13 14.54 10.12 19.22 17.43 16.44 16.23 23.60 19.34 12.19 17.42
#> 63.1 58 92.1 99.1 123.1 113.1 78 55.1 190.1 128 10 149.1 140
#> 22.77 19.34 22.92 21.19 13.00 22.86 23.88 19.34 20.81 20.35 10.53 8.37 12.68
#> 49.1 99.2 184 13 108.1 158 153 56.1 42 107 158.1 168.1 113.2
#> 12.19 21.19 17.77 14.34 18.29 20.14 21.33 12.21 12.43 11.18 20.14 23.72 22.86
#> 130.1 155 139 63.2 90 36 140.1 101.1 181 29 149.2 105 99.3
#> 16.47 13.08 21.49 22.77 20.94 21.19 12.68 9.97 16.46 15.45 8.37 19.75 21.19
#> 40 128.1 183 97 96.1 187.1 111 36.1 179 100 139.1 49.2 16
#> 18.00 20.35 9.24 19.14 14.54 9.92 17.45 21.19 18.63 16.07 21.49 12.19 8.71
#> 152 31 65 112 138 144 80 9 3 98 135 135.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84 1 147 34 34.1 74 200 7 48 17 19 185 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.1 72 163 83.1 17.1 9.1 132 21 163.1 146 48.1 186 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 54 53 22 95 62 141 35 118 38.1 74.1 54.1 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1 174 48.2 112.1 121.1 102 143.1 176 2 162 84.1 1.1 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27 94 46 122 75 172 28 178 147.1 62.1 67 200.1 135.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176.1 47 119.1 163.2 185.1 46.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[46]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004782789 0.500356769 0.539028515
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.384283666 0.007053887 0.166111928
#> grade_iii, Cure model
#> 0.426930959
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 40 18.00 1 28 1 0
#> 68 20.62 1 44 0 0
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 171 16.57 1 41 0 1
#> 154 12.63 1 20 1 0
#> 106 16.67 1 49 1 0
#> 76 19.22 1 54 0 1
#> 15 22.68 1 48 0 0
#> 100 16.07 1 60 0 0
#> 100.1 16.07 1 60 0 0
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 111 17.45 1 47 0 1
#> 88 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 197 21.60 1 69 1 0
#> 106.1 16.67 1 49 1 0
#> 113 22.86 1 34 0 0
#> 41 18.02 1 40 1 0
#> 8 18.43 1 32 0 0
#> 134 17.81 1 47 1 0
#> 15.1 22.68 1 48 0 0
#> 43.1 12.10 1 61 0 1
#> 166 19.98 1 48 0 0
#> 13 14.34 1 54 0 1
#> 117 17.46 1 26 0 1
#> 70 7.38 1 30 1 0
#> 157 15.10 1 47 0 0
#> 85 16.44 1 36 0 0
#> 100.2 16.07 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 128 20.35 1 35 0 1
#> 51 18.23 1 83 0 1
#> 50 10.02 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 57 14.46 1 45 0 1
#> 181 16.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 199 19.81 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 14 12.89 1 21 0 0
#> 183 9.24 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 195.2 11.76 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 130 16.47 1 53 0 1
#> 177 12.53 1 75 0 0
#> 125 15.65 1 67 1 0
#> 188 16.16 1 46 0 1
#> 111.1 17.45 1 47 0 1
#> 39 15.59 1 37 0 1
#> 125.1 15.65 1 67 1 0
#> 8.1 18.43 1 32 0 0
#> 117.1 17.46 1 26 0 1
#> 32 20.90 1 37 1 0
#> 13.1 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 13.2 14.34 1 54 0 1
#> 55 19.34 1 69 0 1
#> 106.2 16.67 1 49 1 0
#> 117.2 17.46 1 26 0 1
#> 92 22.92 1 47 0 1
#> 181.1 16.46 1 45 0 1
#> 106.3 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 190 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 199.1 19.81 1 NA 0 1
#> 181.2 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 41.1 18.02 1 40 1 0
#> 4.1 17.64 1 NA 0 1
#> 106.4 16.67 1 49 1 0
#> 43.2 12.10 1 61 0 1
#> 32.1 20.90 1 37 1 0
#> 170.1 19.54 1 43 0 1
#> 10 10.53 1 34 0 0
#> 60.1 13.15 1 38 1 0
#> 52 10.42 1 52 0 1
#> 30.1 17.43 1 78 0 0
#> 51.1 18.23 1 83 0 1
#> 175 21.91 1 43 0 0
#> 88.1 18.37 1 47 0 0
#> 168.1 23.72 1 70 0 0
#> 124.1 9.73 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 166.1 19.98 1 48 0 0
#> 107 11.18 1 54 1 0
#> 85.1 16.44 1 36 0 0
#> 89.1 11.44 1 NA 0 0
#> 32.2 20.90 1 37 1 0
#> 154.1 12.63 1 20 1 0
#> 88.2 18.37 1 47 0 0
#> 41.2 18.02 1 40 1 0
#> 29.1 15.45 1 68 1 0
#> 14.2 12.89 1 21 0 0
#> 52.1 10.42 1 52 0 1
#> 117.3 17.46 1 26 0 1
#> 108 18.29 1 39 0 1
#> 79 16.23 1 54 1 0
#> 125.2 15.65 1 67 1 0
#> 140.1 12.68 1 59 1 0
#> 41.3 18.02 1 40 1 0
#> 56 12.21 1 60 0 0
#> 42 12.43 1 49 0 1
#> 19 24.00 0 57 0 1
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 47 24.00 0 38 0 1
#> 19.1 24.00 0 57 0 1
#> 138 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 120 24.00 0 68 0 1
#> 137 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 21 24.00 0 47 0 0
#> 94 24.00 0 51 0 1
#> 144 24.00 0 28 0 1
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 196 24.00 0 19 0 0
#> 132 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 120.1 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 47.1 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 176 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 84.1 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 21.1 24.00 0 47 0 0
#> 20.1 24.00 0 46 1 0
#> 103.1 24.00 0 56 1 0
#> 44 24.00 0 56 0 0
#> 2 24.00 0 9 0 0
#> 160 24.00 0 31 1 0
#> 120.2 24.00 0 68 0 1
#> 118 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 160.1 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 103.2 24.00 0 56 1 0
#> 200.1 24.00 0 64 0 0
#> 94.1 24.00 0 51 0 1
#> 104 24.00 0 50 1 0
#> 27.1 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 31 24.00 0 36 0 1
#> 200.2 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 122 24.00 0 66 0 0
#> 141 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 135 24.00 0 58 1 0
#> 102.1 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 104.1 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 119.1 24.00 0 17 0 0
#> 82.1 24.00 0 34 0 0
#> 7 24.00 0 37 1 0
#> 196.1 24.00 0 19 0 0
#> 121 24.00 0 57 1 0
#> 44.1 24.00 0 56 0 0
#> 178.1 24.00 0 52 1 0
#> 104.2 24.00 0 50 1 0
#> 33.1 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 162 24.00 0 51 0 0
#> 151.1 24.00 0 42 0 0
#> 83 24.00 0 6 0 0
#> 193.1 24.00 0 45 0 1
#> 146.1 24.00 0 63 1 0
#> 119.2 24.00 0 17 0 0
#> 44.2 24.00 0 56 0 0
#> 28 24.00 0 67 1 0
#> 161 24.00 0 45 0 0
#> 116 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 65 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.384 NA NA NA
#> 2 age, Cure model 0.00705 NA NA NA
#> 3 grade_ii, Cure model 0.166 NA NA NA
#> 4 grade_iii, Cure model 0.427 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00478 NA NA NA
#> 2 grade_ii, Survival model 0.500 NA NA NA
#> 3 grade_iii, Survival model 0.539 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.384284 0.007054 0.166112 0.426931
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 256.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.384283666 0.007053887 0.166111928 0.426930959
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004782789 0.500356769 0.539028515
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.423451383 0.196571671 0.783517785 0.897469295 0.566152503 0.845072102
#> [7] 0.520449961 0.285374366 0.057124551 0.648510331 0.648510331 0.711882811
#> [13] 0.827494908 0.482045994 0.317917313 0.738895954 0.098702053 0.520449961
#> [19] 0.043435153 0.383105777 0.296281698 0.433806328 0.057124551 0.897469295
#> [25] 0.219485729 0.757020514 0.444083457 0.974686215 0.729839251 0.611952453
#> [31] 0.648510331 0.113322031 0.208170469 0.361528553 0.501133402 0.747979225
#> [37] 0.584875618 0.957607098 0.007511953 0.139049565 0.801133874 0.966154095
#> [43] 0.113322031 0.575539220 0.862468807 0.675764124 0.639392432 0.482045994
#> [49] 0.702803147 0.675764124 0.296281698 0.444083457 0.152111401 0.757020514
#> [55] 0.263713606 0.757020514 0.263713606 0.520449961 0.444083457 0.030391096
#> [61] 0.584875618 0.520449961 0.801133874 0.991549720 0.185101470 0.888736231
#> [67] 0.584875618 0.241998325 0.383105777 0.520449961 0.897469295 0.152111401
#> [73] 0.241998325 0.931843312 0.783517785 0.940492938 0.501133402 0.361528553
#> [79] 0.083673685 0.317917313 0.007511953 0.974686215 0.219485729 0.923205719
#> [85] 0.611952453 0.152111401 0.845072102 0.317917313 0.383105777 0.711882811
#> [91] 0.801133874 0.940492938 0.444083457 0.350471904 0.630225413 0.675764124
#> [97] 0.827494908 0.383105777 0.879976398 0.871238266 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 40 68 60 43 171 154 106 76 15 100 100.1 29 140
#> 18.00 20.62 13.15 12.10 16.57 12.63 16.67 19.22 22.68 16.07 16.07 15.45 12.68
#> 111 88 133 197 106.1 113 41 8 134 15.1 43.1 166 13
#> 17.45 18.37 14.65 21.60 16.67 22.86 18.02 18.43 17.81 22.68 12.10 19.98 14.34
#> 117 70 157 85 100.2 153 128 51 30 57 181 101 168
#> 17.46 7.38 15.10 16.44 16.07 21.33 20.35 18.23 17.43 14.46 16.46 9.97 23.72
#> 36 14 183 153.1 130 177 125 188 111.1 39 125.1 8.1 117.1
#> 21.19 12.89 9.24 21.33 16.47 12.53 15.65 16.16 17.45 15.59 15.65 18.43 17.46
#> 32 13.1 58 13.2 55 106.2 117.2 92 181.1 106.3 14.1 77 190
#> 20.90 14.34 19.34 14.34 19.34 16.67 17.46 22.92 16.46 16.67 12.89 7.27 20.81
#> 49 181.2 170 41.1 106.4 43.2 32.1 170.1 10 60.1 52 30.1 51.1
#> 12.19 16.46 19.54 18.02 16.67 12.10 20.90 19.54 10.53 13.15 10.42 17.43 18.23
#> 175 88.1 168.1 70.1 166.1 107 85.1 32.2 154.1 88.2 41.2 29.1 14.2
#> 21.91 18.37 23.72 7.38 19.98 11.18 16.44 20.90 12.63 18.37 18.02 15.45 12.89
#> 52.1 117.3 108 79 125.2 140.1 41.3 56 42 19 11 103 178
#> 10.42 17.46 18.29 16.23 15.65 12.68 18.02 12.21 12.43 24.00 24.00 24.00 24.00
#> 9 72 47 19.1 138 126 20 120 137 200 21 94 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 1 196 132 80 95 119 120.1 193 47.1 146 176 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 82 84 71 84.1 102 21.1 20.1 103.1 44 2 160 120.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 22 160.1 27 103.2 200.1 94.1 104 27.1 33 31 200.2 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 141 74 135 102.1 185 148 104.1 151 119.1 82.1 7 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 44.1 178.1 104.2 33.1 173 162 151.1 83 193.1 146.1 119.2 44.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 161 116 75 65
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[47]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003544828 0.425178256 0.225890441
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.69129112 0.01042298 -0.03139467
#> grade_iii, Cure model
#> 1.20972799
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 166 19.98 1 48 0 0
#> 93 10.33 1 52 0 1
#> 96 14.54 1 33 0 1
#> 129 23.41 1 53 1 0
#> 113 22.86 1 34 0 0
#> 76 19.22 1 54 0 1
#> 154 12.63 1 20 1 0
#> 125.1 15.65 1 67 1 0
#> 16 8.71 1 71 0 1
#> 61 10.12 1 36 0 1
#> 110 17.56 1 65 0 1
#> 61.1 10.12 1 36 0 1
#> 107 11.18 1 54 1 0
#> 63 22.77 1 31 1 0
#> 153 21.33 1 55 1 0
#> 15 22.68 1 48 0 0
#> 168 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 189 10.51 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 189.1 10.51 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 97 19.14 1 65 0 1
#> 60 13.15 1 38 1 0
#> 24 23.89 1 38 0 0
#> 68 20.62 1 44 0 0
#> 175 21.91 1 43 0 0
#> 96.1 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 23 16.92 1 61 0 0
#> 194 22.40 1 38 0 1
#> 128 20.35 1 35 0 1
#> 68.1 20.62 1 44 0 0
#> 179 18.63 1 42 0 0
#> 136.1 21.83 1 43 0 1
#> 129.1 23.41 1 53 1 0
#> 150 20.33 1 48 0 0
#> 192 16.44 1 31 1 0
#> 171 16.57 1 41 0 1
#> 128.1 20.35 1 35 0 1
#> 127 3.53 1 62 0 1
#> 39 15.59 1 37 0 1
#> 61.2 10.12 1 36 0 1
#> 61.3 10.12 1 36 0 1
#> 184 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 164 23.60 1 76 0 1
#> 164.1 23.60 1 76 0 1
#> 114 13.68 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 57 14.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 96.2 14.54 1 33 0 1
#> 76.1 19.22 1 54 0 1
#> 70 7.38 1 30 1 0
#> 16.1 8.71 1 71 0 1
#> 39.1 15.59 1 37 0 1
#> 37 12.52 1 57 1 0
#> 170 19.54 1 43 0 1
#> 187 9.92 1 39 1 0
#> 86 23.81 1 58 0 1
#> 93.1 10.33 1 52 0 1
#> 58 19.34 1 39 0 0
#> 129.2 23.41 1 53 1 0
#> 105.1 19.75 1 60 0 0
#> 42 12.43 1 49 0 1
#> 169 22.41 1 46 0 0
#> 32 20.90 1 37 1 0
#> 45 17.42 1 54 0 1
#> 39.2 15.59 1 37 0 1
#> 125.2 15.65 1 67 1 0
#> 39.3 15.59 1 37 0 1
#> 92.1 22.92 1 47 0 1
#> 114.1 13.68 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 77 7.27 1 67 0 1
#> 50 10.02 1 NA 1 0
#> 145 10.07 1 65 1 0
#> 187.1 9.92 1 39 1 0
#> 69.1 23.23 1 25 0 1
#> 194.1 22.40 1 38 0 1
#> 114.2 13.68 1 NA 0 0
#> 10 10.53 1 34 0 0
#> 195 11.76 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 42.1 12.43 1 49 0 1
#> 136.2 21.83 1 43 0 1
#> 175.1 21.91 1 43 0 0
#> 177 12.53 1 75 0 0
#> 57.1 14.46 1 45 0 1
#> 180 14.82 1 37 0 0
#> 110.1 17.56 1 65 0 1
#> 149 8.37 1 33 1 0
#> 5 16.43 1 51 0 1
#> 76.2 19.22 1 54 0 1
#> 66 22.13 1 53 0 0
#> 58.1 19.34 1 39 0 0
#> 177.1 12.53 1 75 0 0
#> 52 10.42 1 52 0 1
#> 155 13.08 1 26 0 0
#> 15.1 22.68 1 48 0 0
#> 106 16.67 1 49 1 0
#> 113.1 22.86 1 34 0 0
#> 69.2 23.23 1 25 0 1
#> 89 11.44 1 NA 0 0
#> 125.3 15.65 1 67 1 0
#> 100 16.07 1 60 0 0
#> 86.1 23.81 1 58 0 1
#> 133 14.65 1 57 0 0
#> 52.1 10.42 1 52 0 1
#> 182 24.00 0 35 0 0
#> 196 24.00 0 19 0 0
#> 132 24.00 0 55 0 0
#> 122 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 98 24.00 0 34 1 0
#> 35 24.00 0 51 0 0
#> 137 24.00 0 45 1 0
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 126 24.00 0 48 0 0
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 172 24.00 0 41 0 0
#> 38 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 65.1 24.00 0 57 1 0
#> 84.1 24.00 0 39 0 1
#> 12 24.00 0 63 0 0
#> 71 24.00 0 51 0 0
#> 65.2 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 196.1 24.00 0 19 0 0
#> 12.1 24.00 0 63 0 0
#> 80 24.00 0 41 0 0
#> 7 24.00 0 37 1 0
#> 162 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 118 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 148 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 7.1 24.00 0 37 1 0
#> 147 24.00 0 76 1 0
#> 31 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 162.1 24.00 0 51 0 0
#> 162.2 24.00 0 51 0 0
#> 198 24.00 0 66 0 1
#> 75 24.00 0 21 1 0
#> 135 24.00 0 58 1 0
#> 120 24.00 0 68 0 1
#> 116 24.00 0 58 0 1
#> 98.1 24.00 0 34 1 0
#> 53 24.00 0 32 0 1
#> 161 24.00 0 45 0 0
#> 165 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 118.1 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 115.2 24.00 0 NA 1 0
#> 132.1 24.00 0 55 0 0
#> 54 24.00 0 53 1 0
#> 84.2 24.00 0 39 0 1
#> 53.1 24.00 0 32 0 1
#> 94 24.00 0 51 0 1
#> 116.1 24.00 0 58 0 1
#> 103 24.00 0 56 1 0
#> 160.1 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 75.1 24.00 0 21 1 0
#> 152.1 24.00 0 36 0 1
#> 34 24.00 0 36 0 0
#> 193 24.00 0 45 0 1
#> 27 24.00 0 63 1 0
#> 82.1 24.00 0 34 0 0
#> 115.3 24.00 0 NA 1 0
#> 120.1 24.00 0 68 0 1
#> 62 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 35.1 24.00 0 51 0 0
#> 83.1 24.00 0 6 0 0
#> 196.2 24.00 0 19 0 0
#> 94.1 24.00 0 51 0 1
#> 185 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 20 24.00 0 46 1 0
#> 163.1 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 161.1 24.00 0 45 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.691 NA NA NA
#> 2 age, Cure model 0.0104 NA NA NA
#> 3 grade_ii, Cure model -0.0314 NA NA NA
#> 4 grade_iii, Cure model 1.21 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00354 NA NA NA
#> 2 grade_ii, Survival model 0.425 NA NA NA
#> 3 grade_iii, Survival model 0.226 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69129 0.01042 -0.03139 1.20973
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 242.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.69129112 0.01042298 -0.03139467 1.20972799
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003544828 0.425178256 0.225890441
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.582118742 0.359776414 0.862468197 0.684962539 0.075542716 0.149949572
#> [7] 0.417551699 0.759844300 0.582118742 0.945119815 0.881015787 0.484894393
#> [13] 0.881015787 0.815894231 0.168966758 0.283611764 0.178553384 0.040349375
#> [19] 0.562753918 0.369399139 0.731617332 0.293263504 0.446058364 0.741049729
#> [25] 0.006470576 0.312431806 0.236048374 0.684962539 0.255390810 0.514059730
#> [31] 0.207320808 0.331370299 0.312431806 0.455771479 0.255390810 0.075542716
#> [37] 0.350193804 0.543391110 0.533641395 0.331370299 0.990865135 0.619452555
#> [43] 0.881015787 0.881015787 0.465513320 0.825230268 0.052889011 0.052889011
#> [49] 0.103895804 0.712901368 0.131205107 0.684962539 0.417551699 0.972595357
#> [55] 0.945119815 0.619452555 0.787895884 0.388583096 0.926820037 0.020317093
#> [61] 0.862468197 0.398278016 0.075542716 0.369399139 0.797273201 0.197523643
#> [67] 0.302899464 0.504279066 0.619452555 0.582118742 0.619452555 0.131205107
#> [73] 0.656564860 0.981729755 0.917563495 0.926820037 0.103895804 0.207320808
#> [79] 0.834561044 0.465513320 0.797273201 0.255390810 0.236048374 0.769197562
#> [85] 0.712901368 0.666011645 0.484894393 0.963428630 0.553076421 0.417551699
#> [91] 0.226286425 0.398278016 0.769197562 0.843903681 0.750441833 0.178553384
#> [97] 0.523876719 0.149949572 0.103895804 0.582118742 0.572420639 0.020317093
#> [103] 0.675474933 0.843903681 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 125 166 93 96 129 113 76 154 125.1 16 61 110 61.1
#> 15.65 19.98 10.33 14.54 23.41 22.86 19.22 12.63 15.65 8.71 10.12 17.56 10.12
#> 107 63 153 15 168 188 105 81 90 97 60 24 68
#> 11.18 22.77 21.33 22.68 23.72 16.16 19.75 14.06 20.94 19.14 13.15 23.89 20.62
#> 175 96.1 136 23 194 128 68.1 179 136.1 129.1 150 192 171
#> 21.91 14.54 21.83 16.92 22.40 20.35 20.62 18.63 21.83 23.41 20.33 16.44 16.57
#> 128.1 127 39 61.2 61.3 184 159 164 164.1 69 57 92 96.2
#> 20.35 3.53 15.59 10.12 10.12 17.77 10.55 23.60 23.60 23.23 14.46 22.92 14.54
#> 76.1 70 16.1 39.1 37 170 187 86 93.1 58 129.2 105.1 42
#> 19.22 7.38 8.71 15.59 12.52 19.54 9.92 23.81 10.33 19.34 23.41 19.75 12.43
#> 169 32 45 39.2 125.2 39.3 92.1 167 77 145 187.1 69.1 194.1
#> 22.41 20.90 17.42 15.59 15.65 15.59 22.92 15.55 7.27 10.07 9.92 23.23 22.40
#> 10 184.1 42.1 136.2 175.1 177 57.1 180 110.1 149 5 76.2 66
#> 10.53 17.77 12.43 21.83 21.91 12.53 14.46 14.82 17.56 8.37 16.43 19.22 22.13
#> 58.1 177.1 52 155 15.1 106 113.1 69.2 125.3 100 86.1 133 52.1
#> 19.34 12.53 10.42 13.08 22.68 16.67 22.86 23.23 15.65 16.07 23.81 14.65 10.42
#> 182 196 132 122 152 21 98 35 137 186 65 84 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 2 172 38 182.1 65.1 84.1 12 71 65.2 160 196.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 7 162 141 118 200 148 131 47 83 7.1 147 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 74 162.1 162.2 198 75 135 120 116 98.1 53 161 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 118.1 132.1 54 84.2 53.1 94 116.1 103 160.1 141.1 82 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 34 193 27 82.1 120.1 62 33 174 35.1 83.1 196.2 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 112 20 163.1 19 161.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[48]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001580815 0.922041304 0.550789976
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.21392293 0.02289987 -0.16821605
#> grade_iii, Cure model
#> 1.05350308
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 101 9.97 1 10 0 1
#> 61 10.12 1 36 0 1
#> 164 23.60 1 76 0 1
#> 113 22.86 1 34 0 0
#> 181 16.46 1 45 0 1
#> 170 19.54 1 43 0 1
#> 199 19.81 1 NA 0 1
#> 77 7.27 1 67 0 1
#> 79 16.23 1 54 1 0
#> 88 18.37 1 47 0 0
#> 159 10.55 1 50 0 1
#> 69 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 136 21.83 1 43 0 1
#> 66 22.13 1 53 0 0
#> 78 23.88 1 43 0 0
#> 39 15.59 1 37 0 1
#> 49 12.19 1 48 1 0
#> 159.1 10.55 1 50 0 1
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 29 15.45 1 68 1 0
#> 56 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 195 11.76 1 NA 1 0
#> 199.1 19.81 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 24 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 129 23.41 1 53 1 0
#> 41 18.02 1 40 1 0
#> 157 15.10 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 167 15.55 1 56 1 0
#> 169 22.41 1 46 0 0
#> 124 9.73 1 NA 1 0
#> 125 15.65 1 67 1 0
#> 180 14.82 1 37 0 0
#> 170.1 19.54 1 43 0 1
#> 188 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 188.1 16.16 1 46 0 1
#> 68 20.62 1 44 0 0
#> 130.1 16.47 1 53 0 1
#> 111 17.45 1 47 0 1
#> 6 15.64 1 39 0 0
#> 169.1 22.41 1 46 0 0
#> 128 20.35 1 35 0 1
#> 128.1 20.35 1 35 0 1
#> 91 5.33 1 61 0 1
#> 90 20.94 1 50 0 1
#> 49.1 12.19 1 48 1 0
#> 59 10.16 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 6.1 15.64 1 39 0 0
#> 79.1 16.23 1 54 1 0
#> 188.2 16.16 1 46 0 1
#> 85 16.44 1 36 0 0
#> 105 19.75 1 60 0 0
#> 168 23.72 1 70 0 0
#> 56.1 12.21 1 60 0 0
#> 149.1 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 195.1 11.76 1 NA 1 0
#> 81 14.06 1 34 0 0
#> 170.2 19.54 1 43 0 1
#> 81.1 14.06 1 34 0 0
#> 101.1 9.97 1 10 0 1
#> 158 20.14 1 74 1 0
#> 124.1 9.73 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 92 22.92 1 47 0 1
#> 189 10.51 1 NA 1 0
#> 127.1 3.53 1 62 0 1
#> 63 22.77 1 31 1 0
#> 175 21.91 1 43 0 0
#> 187 9.92 1 39 1 0
#> 181.1 16.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 51.2 18.23 1 83 0 1
#> 150.1 20.33 1 48 0 0
#> 171 16.57 1 41 0 1
#> 194 22.40 1 38 0 1
#> 58 19.34 1 39 0 0
#> 150.2 20.33 1 48 0 0
#> 181.2 16.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 78.1 23.88 1 43 0 0
#> 81.2 14.06 1 34 0 0
#> 16 8.71 1 71 0 1
#> 192 16.44 1 31 1 0
#> 189.1 10.51 1 NA 1 0
#> 123 13.00 1 44 1 0
#> 111.1 17.45 1 47 0 1
#> 179 18.63 1 42 0 0
#> 5.1 16.43 1 51 0 1
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 91.1 5.33 1 61 0 1
#> 177.1 12.53 1 75 0 0
#> 128.2 20.35 1 35 0 1
#> 70 7.38 1 30 1 0
#> 195.2 11.76 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 106 16.67 1 49 1 0
#> 169.2 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 111.2 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 185 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 83 24.00 0 6 0 0
#> 182 24.00 0 35 0 0
#> 7 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 7.1 24.00 0 37 1 0
#> 71 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 198 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 2 24.00 0 9 0 0
#> 35 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 119 24.00 0 17 0 0
#> 162 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 12 24.00 0 63 0 0
#> 116 24.00 0 58 0 1
#> 126 24.00 0 48 0 0
#> 118 24.00 0 44 1 0
#> 198.1 24.00 0 66 0 1
#> 144 24.00 0 28 0 1
#> 31 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 80 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 148 24.00 0 61 1 0
#> 17 24.00 0 38 0 1
#> 80.1 24.00 0 41 0 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 80.2 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 161.1 24.00 0 45 0 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 73 24.00 0 NA 0 1
#> 22.1 24.00 0 52 1 0
#> 67.1 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 148.1 24.00 0 61 1 0
#> 112.1 24.00 0 61 0 0
#> 148.2 24.00 0 61 1 0
#> 144.1 24.00 0 28 0 1
#> 72.1 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 148.3 24.00 0 61 1 0
#> 54 24.00 0 53 1 0
#> 119.1 24.00 0 17 0 0
#> 193 24.00 0 45 0 1
#> 20 24.00 0 46 1 0
#> 19 24.00 0 57 0 1
#> 115 24.00 0 NA 1 0
#> 196 24.00 0 19 0 0
#> 34 24.00 0 36 0 0
#> 2.1 24.00 0 9 0 0
#> 174 24.00 0 49 1 0
#> 135 24.00 0 58 1 0
#> 17.1 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 152.1 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 112.2 24.00 0 61 0 0
#> 121.1 24.00 0 57 1 0
#> 104 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 102.1 24.00 0 49 0 0
#> 109 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 1.1 24.00 0 23 1 0
#> 196.1 24.00 0 19 0 0
#> 82.1 24.00 0 34 0 0
#> 12.1 24.00 0 63 0 0
#> 53.1 24.00 0 32 0 1
#> 151 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.21 NA NA NA
#> 2 age, Cure model 0.0229 NA NA NA
#> 3 grade_ii, Cure model -0.168 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00158 NA NA NA
#> 2 grade_ii, Survival model 0.922 NA NA NA
#> 3 grade_iii, Survival model 0.551 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.2139 0.0229 -0.1682 1.0535
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254.3
#> Residual Deviance: 236.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.21392293 0.02289987 -0.16821605 1.05350308
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001580815 0.922041304 0.550789976
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.92426612 0.91809310 0.14236065 0.22140997 0.65022202 0.46866789
#> [7] 0.97173816 0.70609264 0.53115225 0.89943700 0.18655002 0.57993085
#> [13] 0.33705684 0.30905233 0.06048323 0.76465338 0.87391550 0.89943700
#> [19] 0.54151089 0.63338970 0.77888003 0.86065955 0.69045477 0.84738325
#> [25] 0.94850006 0.02358636 0.91188517 0.16695251 0.57040630 0.78582289
#> [31] 0.51038957 0.77182397 0.25311951 0.74302980 0.79276102 0.46866789
#> [37] 0.72115078 0.98879641 0.41148434 0.72115078 0.36361842 0.63338970
#> [43] 0.58931327 0.75026678 0.25311951 0.37664498 0.37664498 0.97747567
#> [49] 0.35055821 0.87391550 0.84070567 0.75026678 0.70609264 0.72115078
#> [55] 0.67449881 0.45739508 0.11294046 0.86065955 0.94850006 0.79969549
#> [61] 0.81350216 0.46866789 0.81350216 0.92426612 0.44609457 0.54151089
#> [67] 0.20462294 0.98879641 0.23812764 0.32307588 0.93644731 0.65022202
#> [73] 0.88683583 0.54151089 0.41148434 0.62471112 0.29497306 0.49980239
#> [79] 0.41148434 0.65022202 0.88683583 0.06048323 0.81350216 0.94249181
#> [85] 0.67449881 0.83393341 0.58931327 0.52077801 0.69045477 0.97747567
#> [91] 0.84738325 0.37664498 0.96023414 0.96023414 0.61592874 0.25311951
#> [97] 0.80662430 0.58931327 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 101 61 164 113 181 170 77 79 88 159 69 110 136
#> 9.97 10.12 23.60 22.86 16.46 19.54 7.27 16.23 18.37 10.55 23.23 17.56 21.83
#> 66 78 39 49 159.1 51 130 29 56 5 177 149 24
#> 22.13 23.88 15.59 12.19 10.55 18.23 16.47 15.45 12.21 16.43 12.53 8.37 23.89
#> 52 129 41 157 97 167 169 125 180 170.1 188 127 150
#> 10.42 23.41 18.02 15.10 19.14 15.55 22.41 15.65 14.82 19.54 16.16 3.53 20.33
#> 188.1 68 130.1 111 6 169.1 128 128.1 91 90 49.1 140 6.1
#> 16.16 20.62 16.47 17.45 15.64 22.41 20.35 20.35 5.33 20.94 12.19 12.68 15.64
#> 79.1 188.2 85 105 168 56.1 149.1 133 81 170.2 81.1 101.1 158
#> 16.23 16.16 16.44 19.75 23.72 12.21 8.37 14.65 14.06 19.54 14.06 9.97 20.14
#> 51.1 92 127.1 63 175 187 181.1 107 51.2 150.1 171 194 58
#> 18.23 22.92 3.53 22.77 21.91 9.92 16.46 11.18 18.23 20.33 16.57 22.40 19.34
#> 150.2 181.2 107.1 78.1 81.2 16 192 123 111.1 179 5.1 91.1 177.1
#> 20.33 16.46 11.18 23.88 14.06 8.71 16.44 13.00 17.45 18.63 16.43 5.33 12.53
#> 128.2 70 70.1 106 169.2 57 111.2 185 156 103 72 112 83
#> 20.35 7.38 7.38 16.67 22.41 14.46 17.45 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 7 9 161 7.1 71 121 198 65 67 2 35 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119 162 82 12 116 126 118 198.1 144 31 64 80 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 22 148 17 80.1 131 120 143 80.2 152 161.1 75 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 67.1 9.1 162.1 118.1 103.1 148.1 112.1 148.2 144.1 72.1 53 148.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 119.1 193 20 19 196 34 2.1 174 135 17.1 102 152.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182.1 200 112.2 121.1 104 186 102.1 109 191 1.1 196.1 82.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 151
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[49]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.009147829 0.669479084 0.897875965
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.012763539 0.005577467 -0.224280172
#> grade_iii, Cure model
#> 0.131494156
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 192 16.44 1 31 1 0
#> 76 19.22 1 54 0 1
#> 157 15.10 1 47 0 0
#> 113 22.86 1 34 0 0
#> 56 12.21 1 60 0 0
#> 129 23.41 1 53 1 0
#> 51 18.23 1 83 0 1
#> 158 20.14 1 74 1 0
#> 43 12.10 1 61 0 1
#> 183 9.24 1 67 1 0
#> 181 16.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 184 17.77 1 38 0 0
#> 70 7.38 1 30 1 0
#> 192.1 16.44 1 31 1 0
#> 124 9.73 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 188 16.16 1 46 0 1
#> 40 18.00 1 28 1 0
#> 41 18.02 1 40 1 0
#> 106 16.67 1 49 1 0
#> 13 14.34 1 54 0 1
#> 78 23.88 1 43 0 0
#> 32 20.90 1 37 1 0
#> 183.1 9.24 1 67 1 0
#> 6 15.64 1 39 0 0
#> 6.1 15.64 1 39 0 0
#> 32.1 20.90 1 37 1 0
#> 70.1 7.38 1 30 1 0
#> 128 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 134 17.81 1 47 1 0
#> 36 21.19 1 48 0 1
#> 40.1 18.00 1 28 1 0
#> 78.1 23.88 1 43 0 0
#> 149 8.37 1 33 1 0
#> 40.2 18.00 1 28 1 0
#> 55 19.34 1 69 0 1
#> 88 18.37 1 47 0 0
#> 76.1 19.22 1 54 0 1
#> 100 16.07 1 60 0 0
#> 10 10.53 1 34 0 0
#> 52 10.42 1 52 0 1
#> 168 23.72 1 70 0 0
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 190 20.81 1 42 1 0
#> 110 17.56 1 65 0 1
#> 105 19.75 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 78.2 23.88 1 43 0 0
#> 117 17.46 1 26 0 1
#> 177 12.53 1 75 0 0
#> 124.1 9.73 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 79.1 16.23 1 54 1 0
#> 69 23.23 1 25 0 1
#> 177.1 12.53 1 75 0 0
#> 167 15.55 1 56 1 0
#> 101 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 181.1 16.46 1 45 0 1
#> 63.1 22.77 1 31 1 0
#> 66 22.13 1 53 0 0
#> 93 10.33 1 52 0 1
#> 117.1 17.46 1 26 0 1
#> 123 13.00 1 44 1 0
#> 187 9.92 1 39 1 0
#> 179 18.63 1 42 0 0
#> 81 14.06 1 34 0 0
#> 77 7.27 1 67 0 1
#> 100.1 16.07 1 60 0 0
#> 52.1 10.42 1 52 0 1
#> 39 15.59 1 37 0 1
#> 175 21.91 1 43 0 0
#> 8 18.43 1 32 0 0
#> 149.1 8.37 1 33 1 0
#> 68 20.62 1 44 0 0
#> 37 12.52 1 57 1 0
#> 68.1 20.62 1 44 0 0
#> 197.1 21.60 1 69 1 0
#> 78.3 23.88 1 43 0 0
#> 113.1 22.86 1 34 0 0
#> 127 3.53 1 62 0 1
#> 56.1 12.21 1 60 0 0
#> 5 16.43 1 51 0 1
#> 76.2 19.22 1 54 0 1
#> 76.3 19.22 1 54 0 1
#> 129.1 23.41 1 53 1 0
#> 29 15.45 1 68 1 0
#> 128.1 20.35 1 35 0 1
#> 36.1 21.19 1 48 0 1
#> 192.2 16.44 1 31 1 0
#> 43.1 12.10 1 61 0 1
#> 89 11.44 1 NA 0 0
#> 177.2 12.53 1 75 0 0
#> 124.2 9.73 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 175.1 21.91 1 43 0 0
#> 175.2 21.91 1 43 0 0
#> 175.3 21.91 1 43 0 0
#> 179.1 18.63 1 42 0 0
#> 60 13.15 1 38 1 0
#> 52.2 10.42 1 52 0 1
#> 145 10.07 1 65 1 0
#> 24 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 150 20.33 1 48 0 0
#> 192.3 16.44 1 31 1 0
#> 101.1 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 151 24.00 0 42 0 0
#> 80 24.00 0 41 0 0
#> 103 24.00 0 56 1 0
#> 148 24.00 0 61 1 0
#> 120 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 22 24.00 0 52 1 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 126 24.00 0 48 0 0
#> 94.1 24.00 0 51 0 1
#> 121.1 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 173 24.00 0 19 0 1
#> 94.2 24.00 0 51 0 1
#> 126.1 24.00 0 48 0 0
#> 65 24.00 0 57 1 0
#> 161 24.00 0 45 0 0
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 147 24.00 0 76 1 0
#> 119 24.00 0 17 0 0
#> 21 24.00 0 47 0 0
#> 53 24.00 0 32 0 1
#> 104 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#> 38 24.00 0 31 1 0
#> 47 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 82.1 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 141 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 19 24.00 0 57 0 1
#> 11.1 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 67 24.00 0 25 0 0
#> 1 24.00 0 23 1 0
#> 141.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 28.1 24.00 0 67 1 0
#> 94.3 24.00 0 51 0 1
#> 126.2 24.00 0 48 0 0
#> 44 24.00 0 56 0 0
#> 84.1 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 38.1 24.00 0 31 1 0
#> 73.1 24.00 0 NA 0 1
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 64 24.00 0 43 0 0
#> 174.1 24.00 0 49 1 0
#> 147.1 24.00 0 76 1 0
#> 48.1 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 126.3 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 28.2 24.00 0 67 1 0
#> 185 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 74.1 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 186.1 24.00 0 45 1 0
#> 73.2 24.00 0 NA 0 1
#> 84.2 24.00 0 39 0 1
#> 146 24.00 0 63 1 0
#> 116.2 24.00 0 58 0 1
#> 1.1 24.00 0 23 1 0
#> 87.2 24.00 0 27 0 0
#> 161.1 24.00 0 45 0 0
#> 73.3 24.00 0 NA 0 1
#> 20 24.00 0 46 1 0
#> 142 24.00 0 53 0 0
#> 75 24.00 0 21 1 0
#> 84.3 24.00 0 39 0 1
#> 147.2 24.00 0 76 1 0
#> 148.1 24.00 0 61 1 0
#> 109.1 24.00 0 48 0 0
#> 135 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0128 NA NA NA
#> 2 age, Cure model 0.00558 NA NA NA
#> 3 grade_ii, Cure model -0.224 NA NA NA
#> 4 grade_iii, Cure model 0.131 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00915 NA NA NA
#> 2 grade_ii, Survival model 0.669 NA NA NA
#> 3 grade_iii, Survival model 0.898 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.012764 0.005577 -0.224280 0.131494
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 259.7
#> Residual Deviance: 258.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.012763539 0.005577467 -0.224280172 0.131494156
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.009147829 0.669479084 0.897875965
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79468409 0.66569994 0.87584488 0.36354088 0.91422045 0.30307913
#> [7] 0.71901115 0.63319917 0.92656022 0.96849821 0.78408132 0.84392375
#> [13] 0.75567113 0.98624834 0.79468409 0.52605959 0.82963004 0.73169813
#> [19] 0.72540501 0.77855926 0.88025777 0.15776002 0.55891705 0.96849821
#> [25] 0.85322734 0.85322734 0.55891705 0.98624834 0.60697889 0.50129779
#> [31] 0.74971357 0.53795766 0.73169813 0.15776002 0.97923950 0.73169813
#> [37] 0.65798667 0.71236650 0.66569994 0.83443036 0.93450107 0.93847379
#> [43] 0.27199293 0.39915666 0.81990349 0.57859283 0.76160924 0.64160557
#> [49] 0.15776002 0.76739189 0.89750896 0.92246562 0.81990349 0.34458063
#> [55] 0.89750896 0.86693506 0.95744532 0.64993219 0.78408132 0.39915666
#> [61] 0.43034218 0.94991485 0.76739189 0.89324622 0.96482599 0.69235266
#> [67] 0.88460480 0.99317984 0.83443036 0.93847379 0.86239705 0.44587062
#> [73] 0.70568840 0.97923950 0.58820775 0.91006104 0.58820775 0.50129779
#> [79] 0.15776002 0.36354088 0.99660933 0.91422045 0.81489454 0.66569994
#> [85] 0.66569994 0.30307913 0.87142001 0.60697889 0.53795766 0.79468409
#> [91] 0.92656022 0.89750896 0.44587062 0.44587062 0.44587062 0.69235266
#> [97] 0.88894404 0.93847379 0.95369897 0.07784394 0.84860876 0.62446297
#> [103] 0.79468409 0.95744532 0.97568697 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 192 76 157 113 56 129 51 158 43 183 181 26 184
#> 16.44 19.22 15.10 22.86 12.21 23.41 18.23 20.14 12.10 9.24 16.46 15.77 17.77
#> 70 192.1 153 188 40 41 106 13 78 32 183.1 6 6.1
#> 7.38 16.44 21.33 16.16 18.00 18.02 16.67 14.34 23.88 20.90 9.24 15.64 15.64
#> 32.1 70.1 128 197 134 36 40.1 78.1 149 40.2 55 88 76.1
#> 20.90 7.38 20.35 21.60 17.81 21.19 18.00 23.88 8.37 18.00 19.34 18.37 19.22
#> 100 10 52 168 63 79 190 110 105 78.2 117 177 49
#> 16.07 10.53 10.42 23.72 22.77 16.23 20.81 17.56 19.75 23.88 17.46 12.53 12.19
#> 79.1 69 177.1 167 101 170 181.1 63.1 66 93 117.1 123 187
#> 16.23 23.23 12.53 15.55 9.97 19.54 16.46 22.77 22.13 10.33 17.46 13.00 9.92
#> 179 81 77 100.1 52.1 39 175 8 149.1 68 37 68.1 197.1
#> 18.63 14.06 7.27 16.07 10.42 15.59 21.91 18.43 8.37 20.62 12.52 20.62 21.60
#> 78.3 113.1 127 56.1 5 76.2 76.3 129.1 29 128.1 36.1 192.2 43.1
#> 23.88 22.86 3.53 12.21 16.43 19.22 19.22 23.41 15.45 20.35 21.19 16.44 12.10
#> 177.2 175.1 175.2 175.3 179.1 60 52.2 145 24 125 150 192.3 101.1
#> 12.53 21.91 21.91 21.91 18.63 13.15 10.42 10.07 23.89 15.65 20.33 16.44 9.97
#> 16 151 80 103 148 120 9 22 121 94 126 94.1 121.1
#> 8.71 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 173 94.2 126.1 65 161 28 74 7 11 147 119 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 104 65.1 38 47 87 162 82 82.1 116 141 48 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 116.1 19 11.1 186 67 1 141.1 28.1 94.3 126.2 44 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137 163 178 38.1 174 109 64 174.1 147.1 48.1 172 126.3 87.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.2 185 200 74.1 72 186.1 84.2 146 116.2 1.1 87.2 161.1 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 75 84.3 147.2 148.1 109.1 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[50]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004822403 0.455995244 0.460724098
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.52463882 0.02295411 0.52151117
#> grade_iii, Cure model
#> 1.22342736
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 59 10.16 1 NA 1 0
#> 184 17.77 1 38 0 0
#> 4 17.64 1 NA 0 1
#> 36 21.19 1 48 0 1
#> 68 20.62 1 44 0 0
#> 155 13.08 1 26 0 0
#> 97 19.14 1 65 0 1
#> 153 21.33 1 55 1 0
#> 61 10.12 1 36 0 1
#> 128 20.35 1 35 0 1
#> 23 16.92 1 61 0 0
#> 106 16.67 1 49 1 0
#> 41 18.02 1 40 1 0
#> 195 11.76 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 89 11.44 1 NA 0 0
#> 61.1 10.12 1 36 0 1
#> 153.1 21.33 1 55 1 0
#> 13 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 105 19.75 1 60 0 0
#> 136 21.83 1 43 0 1
#> 158 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 16 8.71 1 71 0 1
#> 18 15.21 1 49 1 0
#> 171 16.57 1 41 0 1
#> 70 7.38 1 30 1 0
#> 43 12.10 1 61 0 1
#> 197 21.60 1 69 1 0
#> 100 16.07 1 60 0 0
#> 32 20.90 1 37 1 0
#> 155.1 13.08 1 26 0 0
#> 199 19.81 1 NA 0 1
#> 149 8.37 1 33 1 0
#> 88 18.37 1 47 0 0
#> 70.1 7.38 1 30 1 0
#> 70.2 7.38 1 30 1 0
#> 128.1 20.35 1 35 0 1
#> 129 23.41 1 53 1 0
#> 195.1 11.76 1 NA 1 0
#> 10 10.53 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 123 13.00 1 44 1 0
#> 199.1 19.81 1 NA 0 1
#> 181 16.46 1 45 0 1
#> 51 18.23 1 83 0 1
#> 86.1 23.81 1 58 0 1
#> 155.2 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 51.1 18.23 1 83 0 1
#> 52 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 107 11.18 1 54 1 0
#> 59.1 10.16 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 194 22.40 1 38 0 1
#> 184.1 17.77 1 38 0 0
#> 5 16.43 1 51 0 1
#> 50 10.02 1 NA 1 0
#> 13.1 14.34 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 124 9.73 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 23.1 16.92 1 61 0 0
#> 13.2 14.34 1 54 0 1
#> 41.1 18.02 1 40 1 0
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 181.1 16.46 1 45 0 1
#> 91 5.33 1 61 0 1
#> 114.1 13.68 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 96 14.54 1 33 0 1
#> 16.1 8.71 1 71 0 1
#> 70.3 7.38 1 30 1 0
#> 180 14.82 1 37 0 0
#> 117 17.46 1 26 0 1
#> 61.2 10.12 1 36 0 1
#> 134 17.81 1 47 1 0
#> 18.1 15.21 1 49 1 0
#> 32.1 20.90 1 37 1 0
#> 111 17.45 1 47 0 1
#> 199.2 19.81 1 NA 0 1
#> 10.1 10.53 1 34 0 0
#> 79 16.23 1 54 1 0
#> 78 23.88 1 43 0 0
#> 77 7.27 1 67 0 1
#> 8 18.43 1 32 0 0
#> 130.1 16.47 1 53 0 1
#> 41.2 18.02 1 40 1 0
#> 77.1 7.27 1 67 0 1
#> 134.1 17.81 1 47 1 0
#> 78.1 23.88 1 43 0 0
#> 68.2 20.62 1 44 0 0
#> 50.1 10.02 1 NA 1 0
#> 51.2 18.23 1 83 0 1
#> 117.1 17.46 1 26 0 1
#> 114.2 13.68 1 NA 0 0
#> 57.1 14.46 1 45 0 1
#> 76 19.22 1 54 0 1
#> 37 12.52 1 57 1 0
#> 199.3 19.81 1 NA 0 1
#> 108 18.29 1 39 0 1
#> 91.1 5.33 1 61 0 1
#> 107.1 11.18 1 54 1 0
#> 170 19.54 1 43 0 1
#> 133 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 77.2 7.27 1 67 0 1
#> 182 24.00 0 35 0 0
#> 21 24.00 0 47 0 0
#> 80 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 3 24.00 0 31 1 0
#> 38 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 102.1 24.00 0 49 0 0
#> 65 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 53 24.00 0 32 0 1
#> 17 24.00 0 38 0 1
#> 12 24.00 0 63 0 0
#> 196 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 9 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 141 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 21.1 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 31 24.00 0 36 0 1
#> 119 24.00 0 17 0 0
#> 3.1 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 141.1 24.00 0 44 1 0
#> 196.1 24.00 0 19 0 0
#> 46.1 24.00 0 71 0 0
#> 53.1 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 2 24.00 0 9 0 0
#> 151 24.00 0 42 0 0
#> 173 24.00 0 19 0 1
#> 19 24.00 0 57 0 1
#> 1.1 24.00 0 23 1 0
#> 12.1 24.00 0 63 0 0
#> 162.2 24.00 0 51 0 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 75 24.00 0 21 1 0
#> 178 24.00 0 52 1 0
#> 174 24.00 0 49 1 0
#> 33 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 200 24.00 0 64 0 0
#> 147 24.00 0 76 1 0
#> 33.1 24.00 0 53 0 0
#> 84.1 24.00 0 39 0 1
#> 137 24.00 0 45 1 0
#> 176 24.00 0 43 0 1
#> 152.1 24.00 0 36 0 1
#> 22.1 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 173.1 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 196.2 24.00 0 19 0 0
#> 35 24.00 0 51 0 0
#> 163 24.00 0 66 0 0
#> 44 24.00 0 56 0 0
#> 160 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 160.1 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 3.2 24.00 0 31 1 0
#> 31.1 24.00 0 36 0 1
#> 73.1 24.00 0 NA 0 1
#> 118 24.00 0 44 1 0
#> 126 24.00 0 48 0 0
#> 48 24.00 0 31 1 0
#> 48.1 24.00 0 31 1 0
#> 31.2 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 193 24.00 0 45 0 1
#> 22.2 24.00 0 52 1 0
#> 122.1 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 196.3 24.00 0 19 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.52 NA NA NA
#> 2 age, Cure model 0.0230 NA NA NA
#> 3 grade_ii, Cure model 0.522 NA NA NA
#> 4 grade_iii, Cure model 1.22 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00482 NA NA NA
#> 2 grade_ii, Survival model 0.456 NA NA NA
#> 3 grade_iii, Survival model 0.461 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.52464 0.02295 0.52151 1.22343
#>
#> Degrees of Freedom: 180 Total (i.e. Null); 177 Residual
#> Null Deviance: 250.5
#> Residual Deviance: 233.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.52463882 0.02295411 0.52151117 1.22342736
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004822403 0.455995244 0.460724098
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.43725971 0.15504446 0.20048520 0.72737969 0.29914183 0.13166566
#> [7] 0.85233028 0.23327314 0.48872934 0.50925629 0.38569705 0.16697071
#> [13] 0.05201528 0.85233028 0.13166566 0.69856895 0.60980306 0.26601593
#> [19] 0.10598001 0.25497415 0.88984926 0.61975455 0.51957372 0.91797419
#> [25] 0.78541421 0.11891303 0.59982933 0.17869178 0.72737969 0.90858908
#> [31] 0.33195961 0.91797419 0.91797419 0.23327314 0.07853094 0.82368261
#> [37] 0.75632567 0.54996801 0.35399461 0.05201528 0.72737969 0.00693620
#> [43] 0.35399461 0.84276161 0.67904759 0.31001625 0.79505517 0.52982989
#> [49] 0.09257814 0.43725971 0.56990476 0.69856895 0.20048520 0.63934448
#> [55] 0.48872934 0.69856895 0.38569705 0.81412092 0.76606536 0.54996801
#> [61] 0.98174850 0.88040438 0.66913655 0.88984926 0.91797419 0.64924665
#> [67] 0.45804778 0.85233028 0.41663597 0.61975455 0.17869178 0.47846686
#> [73] 0.82368261 0.57991954 0.02305472 0.95440722 0.32096110 0.52982989
#> [79] 0.38569705 0.95440722 0.41663597 0.02305472 0.20048520 0.35399461
#> [85] 0.45804778 0.67904759 0.28820437 0.77575176 0.34303255 0.98174850
#> [91] 0.79505517 0.27717413 0.65917357 0.58989710 0.95440722 0.00000000
#> [97] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000
#>
#> $Time
#> 184 36 68 155 97 153 61 128 23 106 41 90 86
#> 17.77 21.19 20.62 13.08 19.14 21.33 10.12 20.35 16.92 16.67 18.02 20.94 23.81
#> 61.1 153.1 13 29 105 136 158 16 18 171 70 43 197
#> 10.12 21.33 14.34 15.45 19.75 21.83 20.14 8.71 15.21 16.57 7.38 12.10 21.60
#> 100 32 155.1 149 88 70.1 70.2 128.1 129 10 123 181 51
#> 16.07 20.90 13.08 8.37 18.37 7.38 7.38 20.35 23.41 10.53 13.00 16.46 18.23
#> 86.1 155.2 24 51.1 52 57 179 107 130 194 184.1 5 13.1
#> 23.81 13.08 23.89 18.23 10.42 14.46 18.63 11.18 16.47 22.40 17.77 16.43 14.34
#> 68.1 157 23.1 13.2 41.1 159 154 181.1 91 183 96 16.1 70.3
#> 20.62 15.10 16.92 14.34 18.02 10.55 12.63 16.46 5.33 9.24 14.54 8.71 7.38
#> 180 117 61.2 134 18.1 32.1 111 10.1 79 78 77 8 130.1
#> 14.82 17.46 10.12 17.81 15.21 20.90 17.45 10.53 16.23 23.88 7.27 18.43 16.47
#> 41.2 77.1 134.1 78.1 68.2 51.2 117.1 57.1 76 37 108 91.1 107.1
#> 18.02 7.27 17.81 23.88 20.62 18.23 17.46 14.46 19.22 12.52 18.29 5.33 11.18
#> 170 133 188 77.2 182 21 80 1 3 38 102 102.1 65
#> 19.54 14.65 16.16 7.27 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116 53 17 12 196 131 162 84 9 82 141 22 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 67 31 119 3.1 162.1 94 46 152 141.1 196.1 46.1 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 2 151 173 19 1.1 12.1 162.2 142 11 75 178 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33 54 200 147 33.1 84.1 137 176 152.1 22.1 120 173.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 196.2 35 163 44 160 75.1 160.1 119.1 27 7 3.2 31.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 126 48 48.1 31.2 182.1 193 22.2 122.1 83 165 196.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[51]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001671069 0.289684758 -0.079590326
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.32996780 0.01890509 -0.84828859
#> grade_iii, Cure model
#> -0.06339078
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 99 21.19 1 38 0 1
#> 170 19.54 1 43 0 1
#> 113 22.86 1 34 0 0
#> 24 23.89 1 38 0 0
#> 106 16.67 1 49 1 0
#> 134 17.81 1 47 1 0
#> 150 20.33 1 48 0 0
#> 56.1 12.21 1 60 0 0
#> 37 12.52 1 57 1 0
#> 107 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 158 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 13 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 29 15.45 1 68 1 0
#> 68 20.62 1 44 0 0
#> 133 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 190 20.81 1 42 1 0
#> 99.1 21.19 1 38 0 1
#> 25 6.32 1 34 1 0
#> 90 20.94 1 50 0 1
#> 145 10.07 1 65 1 0
#> 113.1 22.86 1 34 0 0
#> 66 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 180 14.82 1 37 0 0
#> 58 19.34 1 39 0 0
#> 43.1 12.10 1 61 0 1
#> 99.2 21.19 1 38 0 1
#> 99.3 21.19 1 38 0 1
#> 88.1 18.37 1 47 0 0
#> 58.1 19.34 1 39 0 0
#> 180.1 14.82 1 37 0 0
#> 159 10.55 1 50 0 1
#> 32 20.90 1 37 1 0
#> 13.1 14.34 1 54 0 1
#> 105 19.75 1 60 0 0
#> 184 17.77 1 38 0 0
#> 127 3.53 1 62 0 1
#> 158.1 20.14 1 74 1 0
#> 14 12.89 1 21 0 0
#> 133.1 14.65 1 57 0 0
#> 154 12.63 1 20 1 0
#> 97 19.14 1 65 0 1
#> 49 12.19 1 48 1 0
#> 68.1 20.62 1 44 0 0
#> 177 12.53 1 75 0 0
#> 52 10.42 1 52 0 1
#> 150.1 20.33 1 48 0 0
#> 111 17.45 1 47 0 1
#> 164 23.60 1 76 0 1
#> 195 11.76 1 NA 1 0
#> 164.1 23.60 1 76 0 1
#> 81 14.06 1 34 0 0
#> 192 16.44 1 31 1 0
#> 81.1 14.06 1 34 0 0
#> 51 18.23 1 83 0 1
#> 124 9.73 1 NA 1 0
#> 32.1 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 108 18.29 1 39 0 1
#> 114 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 157 15.10 1 47 0 0
#> 89 11.44 1 NA 0 0
#> 4 17.64 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 159.1 10.55 1 50 0 1
#> 110 17.56 1 65 0 1
#> 190.1 20.81 1 42 1 0
#> 150.2 20.33 1 48 0 0
#> 170.1 19.54 1 43 0 1
#> 133.2 14.65 1 57 0 0
#> 124.1 9.73 1 NA 1 0
#> 154.1 12.63 1 20 1 0
#> 99.4 21.19 1 38 0 1
#> 50 10.02 1 NA 1 0
#> 76 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 40 18.00 1 28 1 0
#> 139 21.49 1 63 1 0
#> 170.2 19.54 1 43 0 1
#> 130 16.47 1 53 0 1
#> 157.1 15.10 1 47 0 0
#> 180.2 14.82 1 37 0 0
#> 167 15.55 1 56 1 0
#> 63 22.77 1 31 1 0
#> 6.1 15.64 1 39 0 0
#> 107.1 11.18 1 54 1 0
#> 51.1 18.23 1 83 0 1
#> 13.2 14.34 1 54 0 1
#> 130.1 16.47 1 53 0 1
#> 187 9.92 1 39 1 0
#> 69 23.23 1 25 0 1
#> 129 23.41 1 53 1 0
#> 88.2 18.37 1 47 0 0
#> 149.1 8.37 1 33 1 0
#> 66.1 22.13 1 53 0 0
#> 69.1 23.23 1 25 0 1
#> 192.1 16.44 1 31 1 0
#> 164.2 23.60 1 76 0 1
#> 51.2 18.23 1 83 0 1
#> 77 7.27 1 67 0 1
#> 166 19.98 1 48 0 0
#> 24.1 23.89 1 38 0 0
#> 177.1 12.53 1 75 0 0
#> 26 15.77 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 165 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 73 24.00 0 NA 0 1
#> 7 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 31 24.00 0 36 0 1
#> 109 24.00 0 48 0 0
#> 141 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 152 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 74 24.00 0 43 0 1
#> 35 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 165.1 24.00 0 47 0 0
#> 115 24.00 0 NA 1 0
#> 3 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 47 24.00 0 38 0 1
#> 196 24.00 0 19 0 0
#> 31.1 24.00 0 36 0 1
#> 3.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 116 24.00 0 58 0 1
#> 84.1 24.00 0 39 0 1
#> 64 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 156.1 24.00 0 50 1 0
#> 116.1 24.00 0 58 0 1
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 27 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 137 24.00 0 45 1 0
#> 174 24.00 0 49 1 0
#> 1.1 24.00 0 23 1 0
#> 126 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 135 24.00 0 58 1 0
#> 121 24.00 0 57 1 0
#> 27.1 24.00 0 63 1 0
#> 53 24.00 0 32 0 1
#> 191 24.00 0 60 0 1
#> 135.1 24.00 0 58 1 0
#> 163 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 38 24.00 0 31 1 0
#> 27.2 24.00 0 63 1 0
#> 174.1 24.00 0 49 1 0
#> 73.1 24.00 0 NA 0 1
#> 174.2 24.00 0 49 1 0
#> 103 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 137.1 24.00 0 45 1 0
#> 174.3 24.00 0 49 1 0
#> 38.1 24.00 0 31 1 0
#> 135.2 24.00 0 58 1 0
#> 185 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 67 24.00 0 25 0 0
#> 20.1 24.00 0 46 1 0
#> 11 24.00 0 42 0 1
#> 151 24.00 0 42 0 0
#> 143 24.00 0 51 0 0
#> 156.2 24.00 0 50 1 0
#> 135.3 24.00 0 58 1 0
#> 144 24.00 0 28 0 1
#> 1.2 24.00 0 23 1 0
#> 87 24.00 0 27 0 0
#> 103.1 24.00 0 56 1 0
#> 193.1 24.00 0 45 0 1
#> 178 24.00 0 52 1 0
#> 47.1 24.00 0 38 0 1
#> 3.2 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 82 24.00 0 34 0 0
#> 103.2 24.00 0 56 1 0
#> 126.1 24.00 0 48 0 0
#> 116.2 24.00 0 58 0 1
#> 12.1 24.00 0 63 0 0
#> 186 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 174.4 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.330 NA NA NA
#> 2 age, Cure model 0.0189 NA NA NA
#> 3 grade_ii, Cure model -0.848 NA NA NA
#> 4 grade_iii, Cure model -0.0634 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00167 NA NA NA
#> 2 grade_ii, Survival model 0.290 NA NA NA
#> 3 grade_iii, Survival model -0.0796 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.32997 0.01891 -0.84829 -0.06339
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 249.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.32996780 0.01890509 -0.84828859 -0.06339078
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001671069 0.289684758 -0.079590326
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.84970632 0.19637410 0.38342264 0.11588821 0.01757176 0.56951598
#> [7] 0.53277672 0.31646926 0.84970632 0.84114648 0.90039586 0.88355347
#> [13] 0.34531531 0.95884348 0.75501562 0.67695445 0.66810285 0.29678299
#> [19] 0.72915608 0.44924879 0.27699711 0.19637410 0.98354657 0.24579199
#> [25] 0.94217627 0.11588821 0.15144582 0.64138088 0.70320467 0.41141083
#> [31] 0.88355347 0.19637410 0.19637410 0.44924879 0.41141083 0.70320467
#> [37] 0.91709390 0.25658046 0.75501562 0.37386239 0.54197140 0.99177412
#> [43] 0.34531531 0.79817328 0.72915608 0.80687108 0.43974235 0.86670384
#> [49] 0.29678299 0.82403257 0.93379074 0.31646926 0.56033585 0.04491477
#> [55] 0.04491477 0.78086577 0.60581933 0.78086577 0.48647675 0.25658046
#> [61] 0.51417892 0.47702839 0.60581933 0.68575427 0.91709390 0.55115588
#> [67] 0.27699711 0.31646926 0.38342264 0.72915608 0.80687108 0.19637410
#> [73] 0.43022987 0.59670946 0.17405869 0.52351085 0.18537884 0.38342264
#> [79] 0.57863001 0.68575427 0.70320467 0.65919260 0.13951446 0.64138088
#> [85] 0.90039586 0.48647675 0.75501562 0.57863001 0.95052543 0.09199556
#> [91] 0.07930455 0.44924879 0.95884348 0.15144582 0.09199556 0.60581933
#> [97] 0.04491477 0.48647675 0.97529043 0.36427630 0.01757176 0.82403257
#> [103] 0.63239540 0.86670384 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 56 99 170 113 24 106 134 150 56.1 37 107 43 158
#> 12.21 21.19 19.54 22.86 23.89 16.67 17.81 20.33 12.21 12.52 11.18 12.10 20.14
#> 149 13 18 29 68 133 88 190 99.1 25 90 145 113.1
#> 8.37 14.34 15.21 15.45 20.62 14.65 18.37 20.81 21.19 6.32 20.94 10.07 22.86
#> 66 6 180 58 43.1 99.2 99.3 88.1 58.1 180.1 159 32 13.1
#> 22.13 15.64 14.82 19.34 12.10 21.19 21.19 18.37 19.34 14.82 10.55 20.90 14.34
#> 105 184 127 158.1 14 133.1 154 97 49 68.1 177 52 150.1
#> 19.75 17.77 3.53 20.14 12.89 14.65 12.63 19.14 12.19 20.62 12.53 10.42 20.33
#> 111 164 164.1 81 192 81.1 51 32.1 41 108 85 157 159.1
#> 17.45 23.60 23.60 14.06 16.44 14.06 18.23 20.90 18.02 18.29 16.44 15.10 10.55
#> 110 190.1 150.2 170.1 133.2 154.1 99.4 76 181 197 40 139 170.2
#> 17.56 20.81 20.33 19.54 14.65 12.63 21.19 19.22 16.46 21.60 18.00 21.49 19.54
#> 130 157.1 180.2 167 63 6.1 107.1 51.1 13.2 130.1 187 69 129
#> 16.47 15.10 14.82 15.55 22.77 15.64 11.18 18.23 14.34 16.47 9.92 23.23 23.41
#> 88.2 149.1 66.1 69.1 192.1 164.2 51.2 77 166 24.1 177.1 26 49.1
#> 18.37 8.37 22.13 23.23 16.44 23.60 18.23 7.27 19.98 23.89 12.53 15.77 12.19
#> 165 9 7 95 17 31 109 141 156 152 83 28 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 84 165.1 3 141.1 1 112 47 196 31.1 3.1 19 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 64 173 156.1 116.1 132 132.1 20 27 12 137 174 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 98 135 121 27.1 53 191 135.1 163 193 38 27.2 174.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.2 103 160 137.1 174.3 38.1 135.2 185 65 67 20.1 11 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 156.2 135.3 144 1.2 87 103.1 193.1 178 47.1 3.2 64.1 82
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.2 126.1 116.2 12.1 186 34 174.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[52]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01662512 1.27017319 0.38983641
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.242727782 0.006399151 -0.167473484
#> grade_iii, Cure model
#> 0.628129313
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 133 14.65 1 57 0 0
#> 105 19.75 1 60 0 0
#> 15 22.68 1 48 0 0
#> 177 12.53 1 75 0 0
#> 179 18.63 1 42 0 0
#> 113 22.86 1 34 0 0
#> 159 10.55 1 50 0 1
#> 117 17.46 1 26 0 1
#> 136 21.83 1 43 0 1
#> 154 12.63 1 20 1 0
#> 175 21.91 1 43 0 0
#> 5 16.43 1 51 0 1
#> 189 10.51 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 50 10.02 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 99 21.19 1 38 0 1
#> 56 12.21 1 60 0 0
#> 6 15.64 1 39 0 0
#> 166 19.98 1 48 0 0
#> 8 18.43 1 32 0 0
#> 183 9.24 1 67 1 0
#> 113.1 22.86 1 34 0 0
#> 15.1 22.68 1 48 0 0
#> 177.1 12.53 1 75 0 0
#> 192 16.44 1 31 1 0
#> 42 12.43 1 49 0 1
#> 183.1 9.24 1 67 1 0
#> 78 23.88 1 43 0 0
#> 5.1 16.43 1 51 0 1
#> 175.1 21.91 1 43 0 0
#> 5.2 16.43 1 51 0 1
#> 78.1 23.88 1 43 0 0
#> 127 3.53 1 62 0 1
#> 183.2 9.24 1 67 1 0
#> 70 7.38 1 30 1 0
#> 124 9.73 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 90 20.94 1 50 0 1
#> 36 21.19 1 48 0 1
#> 127.1 3.53 1 62 0 1
#> 58 19.34 1 39 0 0
#> 79 16.23 1 54 1 0
#> 177.2 12.53 1 75 0 0
#> 107 11.18 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 159.1 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 113.2 22.86 1 34 0 0
#> 134 17.81 1 47 1 0
#> 68 20.62 1 44 0 0
#> 125 15.65 1 67 1 0
#> 194 22.40 1 38 0 1
#> 179.1 18.63 1 42 0 0
#> 90.1 20.94 1 50 0 1
#> 69 23.23 1 25 0 1
#> 100 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 192.1 16.44 1 31 1 0
#> 188 16.16 1 46 0 1
#> 79.1 16.23 1 54 1 0
#> 29 15.45 1 68 1 0
#> 133.1 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 91 5.33 1 61 0 1
#> 128 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 184 17.77 1 38 0 0
#> 124.1 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 106.1 16.67 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 41 18.02 1 40 1 0
#> 39 15.59 1 37 0 1
#> 158 20.14 1 74 1 0
#> 107.1 11.18 1 54 1 0
#> 49 12.19 1 48 1 0
#> 37 12.52 1 57 1 0
#> 18 15.21 1 49 1 0
#> 170.1 19.54 1 43 0 1
#> 134.1 17.81 1 47 1 0
#> 91.1 5.33 1 61 0 1
#> 179.2 18.63 1 42 0 0
#> 150 20.33 1 48 0 0
#> 40 18.00 1 28 1 0
#> 88 18.37 1 47 0 0
#> 153 21.33 1 55 1 0
#> 15.2 22.68 1 48 0 0
#> 36.1 21.19 1 48 0 1
#> 188.1 16.16 1 46 0 1
#> 183.3 9.24 1 67 1 0
#> 113.3 22.86 1 34 0 0
#> 140 12.68 1 59 1 0
#> 89 11.44 1 NA 0 0
#> 149 8.37 1 33 1 0
#> 199 19.81 1 NA 0 1
#> 177.3 12.53 1 75 0 0
#> 40.1 18.00 1 28 1 0
#> 159.2 10.55 1 50 0 1
#> 117.1 17.46 1 26 0 1
#> 92.1 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 188.2 16.16 1 46 0 1
#> 51 18.23 1 83 0 1
#> 128.1 20.35 1 35 0 1
#> 13.1 14.34 1 54 0 1
#> 136.1 21.83 1 43 0 1
#> 114.1 13.68 1 NA 0 0
#> 167 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 78.2 23.88 1 43 0 0
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 3 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 116 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 137 24.00 0 45 1 0
#> 21 24.00 0 47 0 0
#> 143 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 144 24.00 0 28 0 1
#> 126 24.00 0 48 0 0
#> 126.1 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 74 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 65 24.00 0 57 1 0
#> 7 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 102.1 24.00 0 49 0 0
#> 160 24.00 0 31 1 0
#> 162 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 182 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 102.2 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 147 24.00 0 76 1 0
#> 146 24.00 0 63 1 0
#> 200 24.00 0 64 0 0
#> 176 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 72 24.00 0 40 0 1
#> 112 24.00 0 61 0 0
#> 156 24.00 0 50 1 0
#> 160.1 24.00 0 31 1 0
#> 102.3 24.00 0 49 0 0
#> 142 24.00 0 53 0 0
#> 72.1 24.00 0 40 0 1
#> 104 24.00 0 50 1 0
#> 44 24.00 0 56 0 0
#> 147.1 24.00 0 76 1 0
#> 121 24.00 0 57 1 0
#> 152 24.00 0 36 0 1
#> 64.1 24.00 0 43 0 0
#> 95 24.00 0 68 0 1
#> 27 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 47 24.00 0 38 0 1
#> 82 24.00 0 34 0 0
#> 156.1 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 1.1 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 83 24.00 0 6 0 0
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 20 24.00 0 46 1 0
#> 46 24.00 0 71 0 0
#> 138.1 24.00 0 44 1 0
#> 34.1 24.00 0 36 0 0
#> 160.2 24.00 0 31 1 0
#> 47.1 24.00 0 38 0 1
#> 27.1 24.00 0 63 1 0
#> 116.1 24.00 0 58 0 1
#> 200.1 24.00 0 64 0 0
#> 73.1 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 178 24.00 0 52 1 0
#> 120.1 24.00 0 68 0 1
#> 73.2 24.00 0 NA 0 1
#> 121.1 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 120.2 24.00 0 68 0 1
#> 147.2 24.00 0 76 1 0
#> 160.3 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 138.2 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 121.2 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 17.1 24.00 0 38 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.243 NA NA NA
#> 2 age, Cure model 0.00640 NA NA NA
#> 3 grade_ii, Cure model -0.167 NA NA NA
#> 4 grade_iii, Cure model 0.628 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0166 NA NA NA
#> 2 grade_ii, Survival model 1.27 NA NA NA
#> 3 grade_iii, Survival model 0.390 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.242728 0.006399 -0.167473 0.628129
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 251.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.242727782 0.006399151 -0.167473484 0.628129313
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01662512 1.27017319 0.38983641
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9219082 0.7221575 0.4889165 0.9431348 0.7629649 0.4217913 0.9702638
#> [8] 0.8317455 0.5908532 0.9402392 0.5638554 0.8675498 0.7293783 0.3817398
#> [15] 0.6263360 0.9597943 0.9051906 0.7148110 0.7818391 0.9777577 0.4217913
#> [22] 0.4889165 0.9431348 0.8592192 0.9570688 0.9777577 0.1991124 0.8675498
#> [29] 0.5638554 0.8675498 0.1991124 0.9956782 0.9777577 0.9890733 0.3247710
#> [36] 0.6550078 0.6263360 0.9956782 0.7431988 0.8795921 0.9431348 0.9651673
#> [43] 0.8414291 0.9702638 0.7431988 0.4217913 0.8169350 0.6730001 0.9016914
#> [50] 0.5494629 0.7629649 0.6550078 0.3546663 0.8980531 0.5343676 0.8592192
#> [57] 0.8871067 0.8795921 0.9155029 0.9219082 0.8503866 0.9912967 0.6819276
#> [64] 0.9342962 0.8268161 0.9281564 0.8414291 0.8004107 0.9086776 0.7073711
#> [71] 0.9651673 0.9625067 0.9543250 0.9187449 0.7293783 0.8169350 0.9912967
#> [78] 0.7629649 0.6989391 0.8061713 0.7881460 0.6155719 0.4889165 0.6263360
#> [85] 0.8871067 0.9777577 0.4217913 0.9373077 0.9868253 0.9431348 0.8061713
#> [92] 0.9702638 0.8317455 0.3817398 0.7564569 0.8871067 0.7943935 0.6819276
#> [99] 0.9281564 0.5908532 0.9121415 0.8548322 0.1991124 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 133 105 15 177 179 113 159 117 136 154 175 5 170
#> 14.65 19.75 22.68 12.53 18.63 22.86 10.55 17.46 21.83 12.63 21.91 16.43 19.54
#> 92 99 56 6 166 8 183 113.1 15.1 177.1 192 42 183.1
#> 22.92 21.19 12.21 15.64 19.98 18.43 9.24 22.86 22.68 12.53 16.44 12.43 9.24
#> 78 5.1 175.1 5.2 78.1 127 183.2 70 164 90 36 127.1 58
#> 23.88 16.43 21.91 16.43 23.88 3.53 9.24 7.38 23.60 20.94 21.19 3.53 19.34
#> 79 177.2 107 106 159.1 55 113.2 134 68 125 194 179.1 90.1
#> 16.23 12.53 11.18 16.67 10.55 19.34 22.86 17.81 20.62 15.65 22.40 18.63 20.94
#> 69 100 169 192.1 188 79.1 29 133.1 171 91 128 123 184
#> 23.23 16.07 22.41 16.44 16.16 16.23 15.45 14.65 16.57 5.33 20.35 13.00 17.77
#> 13 106.1 41 39 158 107.1 49 37 18 170.1 134.1 91.1 179.2
#> 14.34 16.67 18.02 15.59 20.14 11.18 12.19 12.52 15.21 19.54 17.81 5.33 18.63
#> 150 40 88 153 15.2 36.1 188.1 183.3 113.3 140 149 177.3 40.1
#> 20.33 18.00 18.37 21.33 22.68 21.19 16.16 9.24 22.86 12.68 8.37 12.53 18.00
#> 159.2 117.1 92.1 76 188.2 51 128.1 13.1 136.1 167 130 78.2 151
#> 10.55 17.46 22.92 19.22 16.16 18.23 20.35 14.34 21.83 15.55 16.47 23.88 24.00
#> 193 3 132 116 102 137 21 143 87 144 126 126.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 34 65 7 64 102.1 160 162 120 131 28 182 102.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 147 146 200 176 48 72 112 156 160.1 102.3 142 72.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 44 147.1 121 152 64.1 95 27 162.1 17 47 82 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 1.1 138 148 83 119 62 20 46 138.1 34.1 160.2 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 27.1 116.1 200.1 11 178 120.1 121.1 9 19 120.2 147.2 160.3 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.2 103 121.2 71 17.1
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[53]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003665037 0.416330772 0.540919200
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.558958259 0.006391241 0.124927505
#> grade_iii, Cure model
#> 1.036670790
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 195 11.76 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 99 21.19 1 38 0 1
#> 91 5.33 1 61 0 1
#> 169 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 86 23.81 1 58 0 1
#> 78 23.88 1 43 0 0
#> 6 15.64 1 39 0 0
#> 96 14.54 1 33 0 1
#> 99.1 21.19 1 38 0 1
#> 100 16.07 1 60 0 0
#> 15 22.68 1 48 0 0
#> 197 21.60 1 69 1 0
#> 32 20.90 1 37 1 0
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 170 19.54 1 43 0 1
#> 184 17.77 1 38 0 0
#> 15.1 22.68 1 48 0 0
#> 66 22.13 1 53 0 0
#> 134 17.81 1 47 1 0
#> 179 18.63 1 42 0 0
#> 194 22.40 1 38 0 1
#> 4.1 17.64 1 NA 0 1
#> 5 16.43 1 51 0 1
#> 59 10.16 1 NA 1 0
#> 164 23.60 1 76 0 1
#> 180 14.82 1 37 0 0
#> 154 12.63 1 20 1 0
#> 128 20.35 1 35 0 1
#> 16 8.71 1 71 0 1
#> 108 18.29 1 39 0 1
#> 128.1 20.35 1 35 0 1
#> 153 21.33 1 55 1 0
#> 6.1 15.64 1 39 0 0
#> 110 17.56 1 65 0 1
#> 45 17.42 1 54 0 1
#> 66.1 22.13 1 53 0 0
#> 15.2 22.68 1 48 0 0
#> 183 9.24 1 67 1 0
#> 117 17.46 1 26 0 1
#> 96.1 14.54 1 33 0 1
#> 133 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 55 19.34 1 69 0 1
#> 150 20.33 1 48 0 0
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 195.1 11.76 1 NA 1 0
#> 128.2 20.35 1 35 0 1
#> 13 14.34 1 54 0 1
#> 106 16.67 1 49 1 0
#> 57 14.46 1 45 0 1
#> 45.1 17.42 1 54 0 1
#> 61 10.12 1 36 0 1
#> 97 19.14 1 65 0 1
#> 59.1 10.16 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 91.1 5.33 1 61 0 1
#> 194.1 22.40 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 130 16.47 1 53 0 1
#> 150.1 20.33 1 48 0 0
#> 23 16.92 1 61 0 0
#> 110.1 17.56 1 65 0 1
#> 92 22.92 1 47 0 1
#> 36.1 21.19 1 48 0 1
#> 175 21.91 1 43 0 0
#> 127 3.53 1 62 0 1
#> 145 10.07 1 65 1 0
#> 63 22.77 1 31 1 0
#> 14 12.89 1 21 0 0
#> 188 16.16 1 46 0 1
#> 199 19.81 1 NA 0 1
#> 150.2 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 150.3 20.33 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 106.1 16.67 1 49 1 0
#> 63.1 22.77 1 31 1 0
#> 79 16.23 1 54 1 0
#> 37 12.52 1 57 1 0
#> 76 19.22 1 54 0 1
#> 106.2 16.67 1 49 1 0
#> 5.1 16.43 1 51 0 1
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 55.1 19.34 1 69 0 1
#> 158 20.14 1 74 1 0
#> 4.2 17.64 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 40 18.00 1 28 1 0
#> 88 18.37 1 47 0 0
#> 77 7.27 1 67 0 1
#> 24 23.89 1 38 0 0
#> 99.2 21.19 1 38 0 1
#> 157 15.10 1 47 0 0
#> 36.2 21.19 1 48 0 1
#> 16.1 8.71 1 71 0 1
#> 194.2 22.40 1 38 0 1
#> 58 19.34 1 39 0 0
#> 166 19.98 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 159.1 10.55 1 50 0 1
#> 101.1 9.97 1 10 0 1
#> 124 9.73 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 43 12.10 1 61 0 1
#> 106.3 16.67 1 49 1 0
#> 45.2 17.42 1 54 0 1
#> 64 24.00 0 43 0 0
#> 12 24.00 0 63 0 0
#> 172 24.00 0 41 0 0
#> 84 24.00 0 39 0 1
#> 71 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 35 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 47 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 22 24.00 0 52 1 0
#> 47.1 24.00 0 38 0 1
#> 87 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 115 24.00 0 NA 1 0
#> 2.1 24.00 0 9 0 0
#> 156 24.00 0 50 1 0
#> 53 24.00 0 32 0 1
#> 22.1 24.00 0 52 1 0
#> 109 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 142 24.00 0 53 0 0
#> 71.1 24.00 0 51 0 0
#> 80 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 185 24.00 0 44 1 0
#> 3 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 120 24.00 0 68 0 1
#> 147 24.00 0 76 1 0
#> 191 24.00 0 60 0 1
#> 9 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 87.1 24.00 0 27 0 0
#> 118 24.00 0 44 1 0
#> 47.2 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 138 24.00 0 44 1 0
#> 112 24.00 0 61 0 0
#> 95.1 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 80.1 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 95.2 24.00 0 68 0 1
#> 118.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 35.1 24.00 0 51 0 0
#> 74 24.00 0 43 0 1
#> 31.1 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 35.2 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 174.1 24.00 0 49 1 0
#> 19 24.00 0 57 0 1
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 118.2 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 115.1 24.00 0 NA 1 0
#> 71.2 24.00 0 51 0 0
#> 21 24.00 0 47 0 0
#> 44 24.00 0 56 0 0
#> 116 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 103.1 24.00 0 56 1 0
#> 116.1 24.00 0 58 0 1
#> 144.1 24.00 0 28 0 1
#> 120.1 24.00 0 68 0 1
#> 2.2 24.00 0 9 0 0
#> 160 24.00 0 31 1 0
#> 3.1 24.00 0 31 1 0
#> 132.1 24.00 0 55 0 0
#> 109.1 24.00 0 48 0 0
#> 161 24.00 0 45 0 0
#> 148 24.00 0 61 1 0
#> 142.1 24.00 0 53 0 0
#> 116.2 24.00 0 58 0 1
#> 102 24.00 0 49 0 0
#> 198 24.00 0 66 0 1
#> 87.2 24.00 0 27 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.559 NA NA NA
#> 2 age, Cure model 0.00639 NA NA NA
#> 3 grade_ii, Cure model 0.125 NA NA NA
#> 4 grade_iii, Cure model 1.04 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00367 NA NA NA
#> 2 grade_ii, Survival model 0.416 NA NA NA
#> 3 grade_iii, Survival model 0.541 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.558958 0.006391 0.124928 1.036671
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.558958259 0.006391241 0.124927505 1.036670790
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003665037 0.416330772 0.540919200
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.42699731 0.98349941 0.29021481 0.70618807 0.90229907 0.13241400
#> [7] 0.07466435 0.81432623 0.84643267 0.42699731 0.80786800 0.24728613
#> [13] 0.39282072 0.48227708 0.42699731 0.91423709 0.58010073 0.67640991
#> [19] 0.24728613 0.34270673 0.66876798 0.62937284 0.30515201 0.78178371
#> [25] 0.15822539 0.83359304 0.87776076 0.50133610 0.95531157 0.64538205
#> [31] 0.50133610 0.41567729 0.81432623 0.68403896 0.71347201 0.34270673
#> [37] 0.24728613 0.94953089 0.69882511 0.84643267 0.84001856 0.17962145
#> [43] 0.58869264 0.52792398 0.38052989 0.49182274 0.50133610 0.86531021
#> [49] 0.74143662 0.85903377 0.71347201 0.92616227 0.62134177 0.96666966
#> [55] 0.98349941 0.30515201 0.07466435 0.77509167 0.52792398 0.73440760
#> [61] 0.68403896 0.19907243 0.42699731 0.36782434 0.99451306 0.93206767
#> [67] 0.21673080 0.87153726 0.80139705 0.52792398 0.89622448 0.52792398
#> [73] 0.39282072 0.74143662 0.21673080 0.79487167 0.88395650 0.61318636
#> [79] 0.74143662 0.78178371 0.76833629 0.92022050 0.58869264 0.56263007
#> [85] 0.93793868 0.66105542 0.63738689 0.97234234 0.03128100 0.42699731
#> [91] 0.82716033 0.42699731 0.95531157 0.30515201 0.58869264 0.57137824
#> [97] 0.97234234 0.90229907 0.93793868 0.65328116 0.89011475 0.74143662
#> [103] 0.71347201 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 99 91 169 111 159 86 78 6 96 99.1 100 15 197
#> 21.19 5.33 22.41 17.45 10.55 23.81 23.88 15.64 14.54 21.19 16.07 22.68 21.60
#> 32 36 10 170 184 15.1 66 134 179 194 5 164 180
#> 20.90 21.19 10.53 19.54 17.77 22.68 22.13 17.81 18.63 22.40 16.43 23.60 14.82
#> 154 128 16 108 128.1 153 6.1 110 45 66.1 15.2 183 117
#> 12.63 20.35 8.71 18.29 20.35 21.33 15.64 17.56 17.42 22.13 22.68 9.24 17.46
#> 96.1 133 129 55 150 136 68 128.2 13 106 57 45.1 61
#> 14.54 14.65 23.41 19.34 20.33 21.83 20.62 20.35 14.34 16.67 14.46 17.42 10.12
#> 97 70 91.1 194.1 78.1 130 150.1 23 110.1 92 36.1 175 127
#> 19.14 7.38 5.33 22.40 23.88 16.47 20.33 16.92 17.56 22.92 21.19 21.91 3.53
#> 145 63 14 188 150.2 107 150.3 197.1 106.1 63.1 79 37 76
#> 10.07 22.77 12.89 16.16 20.33 11.18 20.33 21.60 16.67 22.77 16.23 12.52 19.22
#> 106.2 5.1 171 93 55.1 158 101 40 88 77 24 99.2 157
#> 16.67 16.43 16.57 10.33 19.34 20.14 9.97 18.00 18.37 7.27 23.89 21.19 15.10
#> 36.2 16.1 194.2 58 166 77.1 159.1 101.1 51 43 106.3 45.2 64
#> 21.19 8.71 22.40 19.34 19.98 7.27 10.55 9.97 18.23 12.10 16.67 17.42 24.00
#> 12 172 84 71 12.1 35 2 47 174 22 47.1 87 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 2.1 156 53 22.1 109 103 142 71.1 80 94 34 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 46 186 120 147 191 9 137 87.1 118 47.2 95 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 138 112 95.1 144 80.1 20 95.2 118.1 31 172.1 35.1 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 132 75 35.2 62 174.1 19 119 151 118.2 143 71.2 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 116 122 151.1 103.1 116.1 144.1 120.1 2.2 160 3.1 132.1 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 148 142.1 116.2 102 198 87.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[54]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 8.953913e-05 2.610817e-02 5.070032e-01
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.52800387 0.01395291 -0.33505624
#> grade_iii, Cure model
#> 0.45267318
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 78 23.88 1 43 0 0
#> 85 16.44 1 36 0 0
#> 93 10.33 1 52 0 1
#> 127 3.53 1 62 0 1
#> 150 20.33 1 48 0 0
#> 81 14.06 1 34 0 0
#> 183 9.24 1 67 1 0
#> 76 19.22 1 54 0 1
#> 69 23.23 1 25 0 1
#> 157 15.10 1 47 0 0
#> 30 17.43 1 78 0 0
#> 42 12.43 1 49 0 1
#> 134 17.81 1 47 1 0
#> 188 16.16 1 46 0 1
#> 139 21.49 1 63 1 0
#> 52 10.42 1 52 0 1
#> 55 19.34 1 69 0 1
#> 171 16.57 1 41 0 1
#> 26 15.77 1 49 0 1
#> 66 22.13 1 53 0 0
#> 159 10.55 1 50 0 1
#> 153 21.33 1 55 1 0
#> 105 19.75 1 60 0 0
#> 171.1 16.57 1 41 0 1
#> 36 21.19 1 48 0 1
#> 140 12.68 1 59 1 0
#> 108 18.29 1 39 0 1
#> 57 14.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 153.1 21.33 1 55 1 0
#> 97 19.14 1 65 0 1
#> 81.1 14.06 1 34 0 0
#> 134.1 17.81 1 47 1 0
#> 155 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 24 23.89 1 38 0 0
#> 166 19.98 1 48 0 0
#> 159.1 10.55 1 50 0 1
#> 42.1 12.43 1 49 0 1
#> 153.2 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 159.2 10.55 1 50 0 1
#> 88 18.37 1 47 0 0
#> 145 10.07 1 65 1 0
#> 197 21.60 1 69 1 0
#> 136 21.83 1 43 0 1
#> 60 13.15 1 38 1 0
#> 43 12.10 1 61 0 1
#> 181 16.46 1 45 0 1
#> 30.1 17.43 1 78 0 0
#> 61 10.12 1 36 0 1
#> 113.1 22.86 1 34 0 0
#> 140.1 12.68 1 59 1 0
#> 42.2 12.43 1 49 0 1
#> 124 9.73 1 NA 1 0
#> 171.2 16.57 1 41 0 1
#> 93.1 10.33 1 52 0 1
#> 170 19.54 1 43 0 1
#> 111.1 17.45 1 47 0 1
#> 70 7.38 1 30 1 0
#> 55.1 19.34 1 69 0 1
#> 190 20.81 1 42 1 0
#> 30.2 17.43 1 78 0 0
#> 25 6.32 1 34 1 0
#> 30.3 17.43 1 78 0 0
#> 108.1 18.29 1 39 0 1
#> 61.1 10.12 1 36 0 1
#> 154 12.63 1 20 1 0
#> 63.1 22.77 1 31 1 0
#> 129 23.41 1 53 1 0
#> 127.1 3.53 1 62 0 1
#> 158 20.14 1 74 1 0
#> 8 18.43 1 32 0 0
#> 188.1 16.16 1 46 0 1
#> 127.2 3.53 1 62 0 1
#> 155.1 13.08 1 26 0 0
#> 105.1 19.75 1 60 0 0
#> 129.1 23.41 1 53 1 0
#> 179 18.63 1 42 0 0
#> 171.3 16.57 1 41 0 1
#> 101 9.97 1 10 0 1
#> 29 15.45 1 68 1 0
#> 97.1 19.14 1 65 0 1
#> 179.1 18.63 1 42 0 0
#> 157.1 15.10 1 47 0 0
#> 60.1 13.15 1 38 1 0
#> 36.1 21.19 1 48 0 1
#> 4 17.64 1 NA 0 1
#> 59 10.16 1 NA 1 0
#> 43.1 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 57.1 14.46 1 45 0 1
#> 93.2 10.33 1 52 0 1
#> 51 18.23 1 83 0 1
#> 179.2 18.63 1 42 0 0
#> 189 10.51 1 NA 1 0
#> 86 23.81 1 58 0 1
#> 190.1 20.81 1 42 1 0
#> 184 17.77 1 38 0 0
#> 79 16.23 1 54 1 0
#> 105.2 19.75 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 190.2 20.81 1 42 1 0
#> 85.1 16.44 1 36 0 0
#> 90 20.94 1 50 0 1
#> 60.2 13.15 1 38 1 0
#> 81.2 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 79.1 16.23 1 54 1 0
#> 8.1 18.43 1 32 0 0
#> 6 15.64 1 39 0 0
#> 72 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 53 24.00 0 32 0 1
#> 20 24.00 0 46 1 0
#> 64 24.00 0 43 0 0
#> 122 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 163 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 53.1 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 38 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#> 178 24.00 0 52 1 0
#> 17 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 152 24.00 0 36 0 1
#> 53.2 24.00 0 32 0 1
#> 174 24.00 0 49 1 0
#> 11 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 193.1 24.00 0 45 0 1
#> 38.1 24.00 0 31 1 0
#> 19 24.00 0 57 0 1
#> 141 24.00 0 44 1 0
#> 148 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 11.1 24.00 0 42 0 1
#> 137 24.00 0 45 1 0
#> 112.1 24.00 0 61 0 0
#> 163.2 24.00 0 66 0 0
#> 176.1 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 173 24.00 0 19 0 1
#> 65 24.00 0 57 1 0
#> 71 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 137.1 24.00 0 45 1 0
#> 35 24.00 0 51 0 0
#> 176.2 24.00 0 43 0 1
#> 80 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 161 24.00 0 45 0 0
#> 141.1 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 2 24.00 0 9 0 0
#> 48 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 80.1 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 72.1 24.00 0 40 0 1
#> 34.1 24.00 0 36 0 0
#> 75.1 24.00 0 21 1 0
#> 185.1 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 156 24.00 0 50 1 0
#> 95 24.00 0 68 0 1
#> 120 24.00 0 68 0 1
#> 156.1 24.00 0 50 1 0
#> 74.1 24.00 0 43 0 1
#> 103.1 24.00 0 56 1 0
#> 148.1 24.00 0 61 1 0
#> 178.1 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 118.1 24.00 0 44 1 0
#> 46 24.00 0 71 0 0
#> 156.2 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 74.2 24.00 0 43 0 1
#> 12.1 24.00 0 63 0 0
#> 165 24.00 0 47 0 0
#> 46.1 24.00 0 71 0 0
#> 147 24.00 0 76 1 0
#> 172 24.00 0 41 0 0
#> 165.1 24.00 0 47 0 0
#> 34.2 24.00 0 36 0 0
#> 22 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 186 24.00 0 45 1 0
#> 185.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.528 NA NA NA
#> 2 age, Cure model 0.0140 NA NA NA
#> 3 grade_ii, Cure model -0.335 NA NA NA
#> 4 grade_iii, Cure model 0.453 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0000895 NA NA NA
#> 2 grade_ii, Survival model 0.0261 NA NA NA
#> 3 grade_iii, Survival model 0.507 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52800 0.01395 -0.33506 0.45267
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 260.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.52800387 0.01395291 -0.33505624 0.45267318
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 8.953913e-05 2.610817e-02 5.070032e-01
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.02940313 0.62450804 0.90471788 0.97845110 0.29733772 0.74773345
#> [7] 0.95640978 0.39036657 0.08999999 0.70729435 0.54775183 0.83549812
#> [13] 0.50282366 0.66637840 0.18841969 0.89712055 0.37058464 0.58256232
#> [19] 0.68276568 0.15169282 0.87439355 0.20041383 0.32928404 0.58256232
#> [25] 0.23412030 0.81148714 0.47533707 0.73171824 0.12741552 0.20041383
#> [31] 0.40021716 0.74773345 0.50282366 0.79549430 0.53005328 0.72354638
#> [37] 0.01085361 0.31864034 0.87439355 0.83549812 0.20041383 0.10301673
#> [43] 0.87439355 0.46582835 0.94167073 0.17640114 0.16435598 0.77162491
#> [49] 0.85890586 0.61604062 0.54775183 0.92694805 0.10301673 0.81148714
#> [55] 0.83549812 0.58256232 0.90471788 0.36018065 0.53005328 0.96375853
#> [61] 0.37058464 0.26649328 0.54775183 0.97110564 0.54775183 0.47533707
#> [67] 0.92694805 0.82746996 0.12741552 0.06351715 0.97845110 0.30799514
#> [73] 0.44700343 0.66637840 0.97845110 0.79549430 0.32928404 0.06351715
#> [79] 0.41906228 0.58256232 0.94905919 0.69912032 0.40021716 0.41906228
#> [85] 0.70729435 0.77162491 0.23412030 0.85890586 0.73171824 0.90471788
#> [91] 0.49368048 0.41906228 0.04838991 0.26649328 0.52092376 0.64971781
#> [97] 0.32928404 0.26649328 0.62450804 0.25574967 0.77162491 0.74773345
#> [103] 0.64132662 0.64971781 0.44700343 0.69094317 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000 0.00000000
#>
#> $Time
#> 78 85 93 127 150 81 183 76 69 157 30 42 134
#> 23.88 16.44 10.33 3.53 20.33 14.06 9.24 19.22 23.23 15.10 17.43 12.43 17.81
#> 188 139 52 55 171 26 66 159 153 105 171.1 36 140
#> 16.16 21.49 10.42 19.34 16.57 15.77 22.13 10.55 21.33 19.75 16.57 21.19 12.68
#> 108 57 63 153.1 97 81.1 134.1 155 111 180 24 166 159.1
#> 18.29 14.46 22.77 21.33 19.14 14.06 17.81 13.08 17.45 14.82 23.89 19.98 10.55
#> 42.1 153.2 113 159.2 88 145 197 136 60 43 181 30.1 61
#> 12.43 21.33 22.86 10.55 18.37 10.07 21.60 21.83 13.15 12.10 16.46 17.43 10.12
#> 113.1 140.1 42.2 171.2 93.1 170 111.1 70 55.1 190 30.2 25 30.3
#> 22.86 12.68 12.43 16.57 10.33 19.54 17.45 7.38 19.34 20.81 17.43 6.32 17.43
#> 108.1 61.1 154 63.1 129 127.1 158 8 188.1 127.2 155.1 105.1 129.1
#> 18.29 10.12 12.63 22.77 23.41 3.53 20.14 18.43 16.16 3.53 13.08 19.75 23.41
#> 179 171.3 101 29 97.1 179.1 157.1 60.1 36.1 43.1 57.1 93.2 51
#> 18.63 16.57 9.97 15.45 19.14 18.63 15.10 13.15 21.19 12.10 14.46 10.33 18.23
#> 179.2 86 190.1 184 79 105.2 190.2 85.1 90 60.2 81.2 5 79.1
#> 18.63 23.81 20.81 17.77 16.23 19.75 20.81 16.44 20.94 13.15 14.06 16.43 16.23
#> 8.1 6 72 144 82 53 20 64 122 176 12 163 74
#> 18.43 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 193 116 53.1 119 118 103 38 163.1 1 178 17 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 53.2 174 11 98 193.1 38.1 19 141 148 34 11.1 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 163.2 176.1 146 173 65 71 102 137.1 35 176.2 80 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 141.1 75 2 48 27 80.1 54 72.1 34.1 75.1 185.1 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 95 120 156.1 74.1 103.1 148.1 178.1 84 118.1 46 156.2 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74.2 12.1 165 46.1 147 172 165.1 34.2 22 21 186 185.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[55]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.000216576 0.356089025 0.416365808
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.04221251 0.02151588 -0.26147123
#> grade_iii, Cure model
#> 0.60385942
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 29 15.45 1 68 1 0
#> 36 21.19 1 48 0 1
#> 42 12.43 1 49 0 1
#> 164 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 16 8.71 1 71 0 1
#> 52 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 159 10.55 1 50 0 1
#> 153 21.33 1 55 1 0
#> 32 20.90 1 37 1 0
#> 189 10.51 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 42.1 12.43 1 49 0 1
#> 89 11.44 1 NA 0 0
#> 25 6.32 1 34 1 0
#> 79 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 159.1 10.55 1 50 0 1
#> 179.1 18.63 1 42 0 0
#> 55 19.34 1 69 0 1
#> 25.1 6.32 1 34 1 0
#> 26 15.77 1 49 0 1
#> 97 19.14 1 65 0 1
#> 189.1 10.51 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 45 17.42 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 177.1 12.53 1 75 0 0
#> 57 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 77 7.27 1 67 0 1
#> 70 7.38 1 30 1 0
#> 157 15.10 1 47 0 0
#> 14.1 12.89 1 21 0 0
#> 8 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 92 22.92 1 47 0 1
#> 26.1 15.77 1 49 0 1
#> 77.1 7.27 1 67 0 1
#> 59.2 10.16 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 39 15.59 1 37 0 1
#> 23.1 16.92 1 61 0 0
#> 50 10.02 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 58 19.34 1 39 0 0
#> 168 23.72 1 70 0 0
#> 97.1 19.14 1 65 0 1
#> 63 22.77 1 31 1 0
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 170 19.54 1 43 0 1
#> 179.2 18.63 1 42 0 0
#> 89.1 11.44 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 57.1 14.46 1 45 0 1
#> 166.1 19.98 1 48 0 0
#> 16.1 8.71 1 71 0 1
#> 52.1 10.42 1 52 0 1
#> 150 20.33 1 48 0 0
#> 57.2 14.46 1 45 0 1
#> 111.1 17.45 1 47 0 1
#> 13 14.34 1 54 0 1
#> 6 15.64 1 39 0 0
#> 13.1 14.34 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 68.1 20.62 1 44 0 0
#> 105 19.75 1 60 0 0
#> 18.1 15.21 1 49 1 0
#> 129 23.41 1 53 1 0
#> 66 22.13 1 53 0 0
#> 100 16.07 1 60 0 0
#> 81 14.06 1 34 0 0
#> 89.2 11.44 1 NA 0 0
#> 92.1 22.92 1 47 0 1
#> 16.2 8.71 1 71 0 1
#> 25.2 6.32 1 34 1 0
#> 127 3.53 1 62 0 1
#> 99 21.19 1 38 0 1
#> 130 16.47 1 53 0 1
#> 130.1 16.47 1 53 0 1
#> 180 14.82 1 37 0 0
#> 29.1 15.45 1 68 1 0
#> 189.2 10.51 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 124.1 9.73 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 16.3 8.71 1 71 0 1
#> 52.2 10.42 1 52 0 1
#> 57.3 14.46 1 45 0 1
#> 92.2 22.92 1 47 0 1
#> 6.1 15.64 1 39 0 0
#> 68.2 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 169.1 22.41 1 46 0 0
#> 106 16.67 1 49 1 0
#> 108 18.29 1 39 0 1
#> 134 17.81 1 47 1 0
#> 134.1 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 153.1 21.33 1 55 1 0
#> 89.3 11.44 1 NA 0 0
#> 90 20.94 1 50 0 1
#> 94 24.00 0 51 0 1
#> 2 24.00 0 9 0 0
#> 3 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 148 24.00 0 61 1 0
#> 48 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 72 24.00 0 40 0 1
#> 144 24.00 0 28 0 1
#> 3.1 24.00 0 31 1 0
#> 161.1 24.00 0 45 0 0
#> 185.1 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 156 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 3.2 24.00 0 31 1 0
#> 156.1 24.00 0 50 1 0
#> 54 24.00 0 53 1 0
#> 174 24.00 0 49 1 0
#> 151 24.00 0 42 0 0
#> 142 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 62.1 24.00 0 71 0 0
#> 2.1 24.00 0 9 0 0
#> 146 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 161.2 24.00 0 45 0 0
#> 53 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 102 24.00 0 49 0 0
#> 200.1 24.00 0 64 0 0
#> 82 24.00 0 34 0 0
#> 80 24.00 0 41 0 0
#> 186 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 2.2 24.00 0 9 0 0
#> 198 24.00 0 66 0 1
#> 119 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 144.1 24.00 0 28 0 1
#> 196 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 21 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 161.3 24.00 0 45 0 0
#> 12 24.00 0 63 0 0
#> 119.1 24.00 0 17 0 0
#> 152 24.00 0 36 0 1
#> 152.1 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 173.1 24.00 0 19 0 1
#> 156.2 24.00 0 50 1 0
#> 138 24.00 0 44 1 0
#> 151.1 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 160 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 163.2 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 121 24.00 0 57 1 0
#> 84 24.00 0 39 0 1
#> 19.1 24.00 0 57 0 1
#> 3.3 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 151.2 24.00 0 42 0 0
#> 120.1 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 115.1 24.00 0 NA 1 0
#> 143 24.00 0 51 0 0
#> 95 24.00 0 68 0 1
#> 178.2 24.00 0 52 1 0
#> 103.1 24.00 0 56 1 0
#> 71.1 24.00 0 51 0 0
#> 3.4 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 22 24.00 0 52 1 0
#> 200.2 24.00 0 64 0 0
#> 141 24.00 0 44 1 0
#> 191 24.00 0 60 0 1
#> 21.1 24.00 0 47 0 0
#> 98.1 24.00 0 34 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.04 NA NA NA
#> 2 age, Cure model 0.0215 NA NA NA
#> 3 grade_ii, Cure model -0.261 NA NA NA
#> 4 grade_iii, Cure model 0.604 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000217 NA NA NA
#> 2 grade_ii, Survival model 0.356 NA NA NA
#> 3 grade_iii, Survival model 0.416 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.04221 0.02152 -0.26147 0.60386
#>
#> Degrees of Freedom: 182 Total (i.e. Null); 179 Residual
#> Null Deviance: 253
#> Residual Deviance: 242.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.04221251 0.02151588 -0.26147123 0.60385942
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.000216576 0.356089025 0.416365808
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.68782086 0.79099621 0.67001122 0.25888168 0.83296897 0.09954664
#> [7] 0.22264404 0.91466281 0.88254437 0.06035014 0.86619232 0.23531588
#> [13] 0.29259456 0.44112171 0.90660340 0.81620135 0.83296897 0.96931794
#> [19] 0.59688503 0.30363937 0.86619232 0.44112171 0.40018587 0.96931794
#> [25] 0.62462546 0.42092129 0.54013487 0.54974210 0.81620135 0.73194506
#> [31] 0.79942810 0.95376730 0.94589057 0.70542859 0.79942810 0.47105496
#> [37] 0.35738095 0.13384899 0.62462546 0.95376730 0.02238429 0.66093744
#> [43] 0.54974210 0.02238429 0.40018587 0.07997259 0.42092129 0.17133900
#> [49] 0.84955874 0.38952713 0.44112171 0.18442571 0.52091024 0.73194506
#> [55] 0.35738095 0.91466281 0.88254437 0.33555415 0.73194506 0.52091024
#> [61] 0.76567185 0.64278361 0.76567185 0.47105496 0.30363937 0.37871137
#> [67] 0.68782086 0.11725120 0.20964144 0.60618180 0.78252463 0.13384899
#> [73] 0.91466281 0.96931794 0.99230862 0.25888168 0.57830869 0.57830869
#> [79] 0.71428695 0.67001122 0.85789345 0.60618180 0.91466281 0.88254437
#> [85] 0.73194506 0.13384899 0.64278361 0.30363937 0.72314442 0.18442571
#> [91] 0.56877997 0.49122214 0.50130076 0.50130076 0.34654499 0.23531588
#> [97] 0.28136361 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 18 60 29 36 42 164 139 16 52 86 159 153 32
#> 15.21 13.15 15.45 21.19 12.43 23.60 21.49 8.71 10.42 23.81 10.55 21.33 20.90
#> 179 183 177 42.1 25 79 68 159.1 179.1 55 25.1 26 97
#> 18.63 9.24 12.53 12.43 6.32 16.23 20.62 10.55 18.63 19.34 6.32 15.77 19.14
#> 45 23 177.1 57 14 77 70 157 14.1 8 166 92 26.1
#> 17.42 16.92 12.53 14.46 12.89 7.27 7.38 15.10 12.89 18.43 19.98 22.92 15.77
#> 77.1 24 39 23.1 24.1 58 168 97.1 63 56 170 179.2 169
#> 7.27 23.89 15.59 16.92 23.89 19.34 23.72 19.14 22.77 12.21 19.54 18.63 22.41
#> 111 57.1 166.1 16.1 52.1 150 57.2 111.1 13 6 13.1 8.1 68.1
#> 17.45 14.46 19.98 8.71 10.42 20.33 14.46 17.45 14.34 15.64 14.34 18.43 20.62
#> 105 18.1 129 66 100 81 92.1 16.2 25.2 127 99 130 130.1
#> 19.75 15.21 23.41 22.13 16.07 14.06 22.92 8.71 6.32 3.53 21.19 16.47 16.47
#> 180 29.1 107 100.1 16.3 52.2 57.3 92.2 6.1 68.2 96 169.1 106
#> 14.82 15.45 11.18 16.07 8.71 10.42 14.46 22.92 15.64 20.62 14.54 22.41 16.67
#> 108 134 134.1 158 153.1 90 94 2 3 98 148 48 178
#> 18.29 17.81 17.81 20.14 21.33 20.94 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 185 72 144 3.1 161.1 185.1 178.1 156 74 3.2 156.1 54
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 151 142 71 62 120 62.1 2.1 146 163 200 161.2 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11 173 147 102 200.1 82 80 186 87 2.2 198 119 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 33 21 103 161.3 12 119.1 152 152.1 193 173.1 156.2 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 116 160 163.1 163.2 19 121 84 19.1 3.3 198.1 151.2 120.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 143 95 178.2 103.1 71.1 3.4 64 22 200.2 141 191 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98.1
#> 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[56]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004377317 0.918876663 0.619726789
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.562411656 0.008323881 0.183254295
#> grade_iii, Cure model
#> 0.842189466
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 169 22.41 1 46 0 0
#> 164 23.60 1 76 0 1
#> 175 21.91 1 43 0 0
#> 85 16.44 1 36 0 0
#> 85.1 16.44 1 36 0 0
#> 114 13.68 1 NA 0 0
#> 50 10.02 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 124 9.73 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 66 22.13 1 53 0 0
#> 6 15.64 1 39 0 0
#> 56 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 93 10.33 1 52 0 1
#> 113 22.86 1 34 0 0
#> 128 20.35 1 35 0 1
#> 183 9.24 1 67 1 0
#> 183.1 9.24 1 67 1 0
#> 78 23.88 1 43 0 0
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 123 13.00 1 44 1 0
#> 166 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 145.1 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 89 11.44 1 NA 0 0
#> 14 12.89 1 21 0 0
#> 66.1 22.13 1 53 0 0
#> 16 8.71 1 71 0 1
#> 55 19.34 1 69 0 1
#> 93.1 10.33 1 52 0 1
#> 134.1 17.81 1 47 1 0
#> 127 3.53 1 62 0 1
#> 130 16.47 1 53 0 1
#> 139 21.49 1 63 1 0
#> 111 17.45 1 47 0 1
#> 13 14.34 1 54 0 1
#> 24 23.89 1 38 0 0
#> 13.1 14.34 1 54 0 1
#> 61 10.12 1 36 0 1
#> 159.1 10.55 1 50 0 1
#> 60 13.15 1 38 1 0
#> 85.2 16.44 1 36 0 0
#> 100 16.07 1 60 0 0
#> 114.1 13.68 1 NA 0 0
#> 177 12.53 1 75 0 0
#> 134.2 17.81 1 47 1 0
#> 128.1 20.35 1 35 0 1
#> 100.1 16.07 1 60 0 0
#> 39 15.59 1 37 0 1
#> 58 19.34 1 39 0 0
#> 61.1 10.12 1 36 0 1
#> 136 21.83 1 43 0 1
#> 5.1 16.43 1 51 0 1
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 188 16.16 1 46 0 1
#> 127.1 3.53 1 62 0 1
#> 184 17.77 1 38 0 0
#> 70 7.38 1 30 1 0
#> 91 5.33 1 61 0 1
#> 128.2 20.35 1 35 0 1
#> 5.2 16.43 1 51 0 1
#> 59 10.16 1 NA 1 0
#> 14.1 12.89 1 21 0 0
#> 107 11.18 1 54 1 0
#> 96 14.54 1 33 0 1
#> 88 18.37 1 47 0 0
#> 23 16.92 1 61 0 0
#> 175.1 21.91 1 43 0 0
#> 154 12.63 1 20 1 0
#> 93.2 10.33 1 52 0 1
#> 26 15.77 1 49 0 1
#> 89.1 11.44 1 NA 0 0
#> 125 15.65 1 67 1 0
#> 171 16.57 1 41 0 1
#> 154.1 12.63 1 20 1 0
#> 153 21.33 1 55 1 0
#> 8 18.43 1 32 0 0
#> 18 15.21 1 49 1 0
#> 107.1 11.18 1 54 1 0
#> 89.2 11.44 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 90 20.94 1 50 0 1
#> 86 23.81 1 58 0 1
#> 195 11.76 1 NA 1 0
#> 192 16.44 1 31 1 0
#> 195.1 11.76 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 89.3 11.44 1 NA 0 0
#> 199 19.81 1 NA 0 1
#> 130.1 16.47 1 53 0 1
#> 124.1 9.73 1 NA 1 0
#> 101 9.97 1 10 0 1
#> 96.1 14.54 1 33 0 1
#> 97 19.14 1 65 0 1
#> 177.1 12.53 1 75 0 0
#> 77 7.27 1 67 0 1
#> 149 8.37 1 33 1 0
#> 150 20.33 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 175.2 21.91 1 43 0 0
#> 25 6.32 1 34 1 0
#> 49.1 12.19 1 48 1 0
#> 168 23.72 1 70 0 0
#> 32.1 20.90 1 37 1 0
#> 88.1 18.37 1 47 0 0
#> 39.1 15.59 1 37 0 1
#> 154.2 12.63 1 20 1 0
#> 28 24.00 0 67 1 0
#> 131 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 98 24.00 0 34 1 0
#> 83 24.00 0 6 0 0
#> 73 24.00 0 NA 0 1
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 65 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 54 24.00 0 53 1 0
#> 156 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 62 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 7.1 24.00 0 37 1 0
#> 126 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 131.1 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 53 24.00 0 32 0 1
#> 9 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 176.1 24.00 0 43 0 1
#> 1 24.00 0 23 1 0
#> 156.1 24.00 0 50 1 0
#> 7.2 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 84.2 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 98.1 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 3 24.00 0 31 1 0
#> 9.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 47.1 24.00 0 38 0 1
#> 9.2 24.00 0 31 1 0
#> 178 24.00 0 52 1 0
#> 126.1 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 94 24.00 0 51 0 1
#> 146 24.00 0 63 1 0
#> 142 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 200 24.00 0 64 0 0
#> 33 24.00 0 53 0 0
#> 17 24.00 0 38 0 1
#> 12.1 24.00 0 63 0 0
#> 94.1 24.00 0 51 0 1
#> 191.1 24.00 0 60 0 1
#> 87 24.00 0 27 0 0
#> 67 24.00 0 25 0 0
#> 115 24.00 0 NA 1 0
#> 126.2 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 132.1 24.00 0 55 0 0
#> 102 24.00 0 49 0 0
#> 47.2 24.00 0 38 0 1
#> 65.1 24.00 0 57 1 0
#> 12.2 24.00 0 63 0 0
#> 132.2 24.00 0 55 0 0
#> 156.2 24.00 0 50 1 0
#> 84.3 24.00 0 39 0 1
#> 35.1 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 104 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 11.1 24.00 0 42 0 1
#> 87.1 24.00 0 27 0 0
#> 186 24.00 0 45 1 0
#> 163 24.00 0 66 0 0
#> 83.1 24.00 0 6 0 0
#> 94.2 24.00 0 51 0 1
#> 161 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 147 24.00 0 76 1 0
#> 38 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.562 NA NA NA
#> 2 age, Cure model 0.00832 NA NA NA
#> 3 grade_ii, Cure model 0.183 NA NA NA
#> 4 grade_iii, Cure model 0.842 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00438 NA NA NA
#> 2 grade_ii, Survival model 0.919 NA NA NA
#> 3 grade_iii, Survival model 0.620 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.562412 0.008324 0.183254 0.842189
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.562411656 0.008323881 0.183254295 0.842189466
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004377317 0.918876663 0.619726789
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.12218495 0.07602979 0.16828046 0.53699724 0.53699724 0.84680736
#> [7] 0.92204502 0.13767567 0.64642111 0.80740428 0.42824760 0.86217628
#> [13] 0.10704633 0.30867246 0.92936436 0.92936436 0.02342513 0.89985818
#> [19] 0.57377125 0.74243057 0.35165043 0.44975692 0.89985818 0.81550356
#> [25] 0.75079450 0.13767567 0.94374920 0.36277512 0.86217628 0.44975692
#> [31] 0.98618267 0.51803661 0.23000606 0.48865621 0.71691155 0.00719105
#> [37] 0.71691155 0.88483707 0.84680736 0.73396484 0.53699724 0.61006179
#> [43] 0.79132404 0.44975692 0.30867246 0.61006179 0.66438587 0.36277512
#> [49] 0.88483707 0.21413742 0.57377125 0.27278712 0.29689388 0.43914759
#> [55] 0.60093855 0.98618267 0.47875642 0.95808621 0.97920878 0.30867246
#> [61] 0.57377125 0.75079450 0.83129967 0.69966664 0.40641420 0.49845422
#> [67] 0.16828046 0.76746164 0.86217628 0.62829691 0.63741501 0.50829757
#> [73] 0.76746164 0.24494535 0.39545791 0.68207304 0.83129967 0.09220100
#> [79] 0.25905051 0.04255329 0.53699724 0.69085747 0.51803661 0.91466043
#> [85] 0.69966664 0.38454116 0.79132404 0.96515999 0.95094930 0.34059206
#> [91] 0.64642111 0.16828046 0.97221382 0.81550356 0.05864997 0.27278712
#> [97] 0.40641420 0.66438587 0.76746164 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 169 164 175 85 85.1 159 187 66 6 56 108 93 113
#> 22.41 23.60 21.91 16.44 16.44 10.55 9.92 22.13 15.64 12.21 18.29 10.33 22.86
#> 128 183 183.1 78 145 5 123 166 134 145.1 49 14 66.1
#> 20.35 9.24 9.24 23.88 10.07 16.43 13.00 19.98 17.81 10.07 12.19 12.89 22.13
#> 16 55 93.1 134.1 127 130 139 111 13 24 13.1 61 159.1
#> 8.71 19.34 10.33 17.81 3.53 16.47 21.49 17.45 14.34 23.89 14.34 10.12 10.55
#> 60 85.2 100 177 134.2 128.1 100.1 39 58 61.1 136 5.1 32
#> 13.15 16.44 16.07 12.53 17.81 20.35 16.07 15.59 19.34 10.12 21.83 16.43 20.90
#> 190 41 188 127.1 184 70 91 128.2 5.2 14.1 107 96 88
#> 20.81 18.02 16.16 3.53 17.77 7.38 5.33 20.35 16.43 12.89 11.18 14.54 18.37
#> 23 175.1 154 93.2 26 125 171 154.1 153 8 18 107.1 92
#> 16.92 21.91 12.63 10.33 15.77 15.65 16.57 12.63 21.33 18.43 15.21 11.18 22.92
#> 90 86 192 133 130.1 101 96.1 97 177.1 77 149 150 6.1
#> 20.94 23.81 16.44 14.65 16.47 9.97 14.54 19.14 12.53 7.27 8.37 20.33 15.64
#> 175.2 25 49.1 168 32.1 88.1 39.1 154.2 28 131 173 98 83
#> 21.91 6.32 12.19 23.72 20.90 18.37 15.59 12.63 24.00 24.00 24.00 24.00 24.00
#> 84 84.1 65 21 20 54 156 7 27 119 62 121 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 19 131.1 176 196 53 9 138 35 12 176.1 1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.2 11 84.2 47 98.1 191 46 80 80.1 3 9.1 82 47.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9.2 178 126.1 2 94 146 142 22 200 33 17 12.1 94.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 87 67 126.2 132 132.1 102 47.2 65.1 12.2 132.2 156.2 84.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 44 104 109 11.1 87.1 186 163 83.1 94.2 161 186.1 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 33.1 172
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[57]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00528232 0.57868746 0.29035147
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.64728499 0.01202607 0.42228259
#> grade_iii, Cure model
#> 0.48233550
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 168 23.72 1 70 0 0
#> 37 12.52 1 57 1 0
#> 166 19.98 1 48 0 0
#> 149 8.37 1 33 1 0
#> 181 16.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 13 14.34 1 54 0 1
#> 129 23.41 1 53 1 0
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 81 14.06 1 34 0 0
#> 153.1 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 194 22.40 1 38 0 1
#> 188 16.16 1 46 0 1
#> 183 9.24 1 67 1 0
#> 105 19.75 1 60 0 0
#> 50 10.02 1 NA 1 0
#> 40 18.00 1 28 1 0
#> 39 15.59 1 37 0 1
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 108 18.29 1 39 0 1
#> 37.1 12.52 1 57 1 0
#> 133 14.65 1 57 0 0
#> 32 20.90 1 37 1 0
#> 195 11.76 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 18 15.21 1 49 1 0
#> 180 14.82 1 37 0 0
#> 189 10.51 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 125 15.65 1 67 1 0
#> 59 10.16 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 92 22.92 1 47 0 1
#> 25.1 6.32 1 34 1 0
#> 169 22.41 1 46 0 0
#> 43.1 12.10 1 61 0 1
#> 23 16.92 1 61 0 0
#> 23.1 16.92 1 61 0 0
#> 14 12.89 1 21 0 0
#> 183.1 9.24 1 67 1 0
#> 69 23.23 1 25 0 1
#> 105.1 19.75 1 60 0 0
#> 166.1 19.98 1 48 0 0
#> 24 23.89 1 38 0 0
#> 49 12.19 1 48 1 0
#> 108.1 18.29 1 39 0 1
#> 76 19.22 1 54 0 1
#> 32.1 20.90 1 37 1 0
#> 124 9.73 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 25.2 6.32 1 34 1 0
#> 140.1 12.68 1 59 1 0
#> 8 18.43 1 32 0 0
#> 197 21.60 1 69 1 0
#> 177 12.53 1 75 0 0
#> 159 10.55 1 50 0 1
#> 70 7.38 1 30 1 0
#> 101 9.97 1 10 0 1
#> 42.1 12.43 1 49 0 1
#> 49.1 12.19 1 48 1 0
#> 195.1 11.76 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 24.1 23.89 1 38 0 0
#> 85 16.44 1 36 0 0
#> 14.1 12.89 1 21 0 0
#> 70.1 7.38 1 30 1 0
#> 32.2 20.90 1 37 1 0
#> 16 8.71 1 71 0 1
#> 150 20.33 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 4 17.64 1 NA 0 1
#> 29.1 15.45 1 68 1 0
#> 39.1 15.59 1 37 0 1
#> 81.1 14.06 1 34 0 0
#> 145 10.07 1 65 1 0
#> 97 19.14 1 65 0 1
#> 158 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 145.1 10.07 1 65 1 0
#> 56 12.21 1 60 0 0
#> 49.2 12.19 1 48 1 0
#> 85.1 16.44 1 36 0 0
#> 55.2 19.34 1 69 0 1
#> 45 17.42 1 54 0 1
#> 179 18.63 1 42 0 0
#> 145.2 10.07 1 65 1 0
#> 133.1 14.65 1 57 0 0
#> 49.3 12.19 1 48 1 0
#> 85.2 16.44 1 36 0 0
#> 113.1 22.86 1 34 0 0
#> 8.1 18.43 1 32 0 0
#> 187 9.92 1 39 1 0
#> 129.1 23.41 1 53 1 0
#> 180.1 14.82 1 37 0 0
#> 177.1 12.53 1 75 0 0
#> 97.1 19.14 1 65 0 1
#> 55.3 19.34 1 69 0 1
#> 167 15.55 1 56 1 0
#> 194.1 22.40 1 38 0 1
#> 50.1 10.02 1 NA 1 0
#> 107 11.18 1 54 1 0
#> 14.2 12.89 1 21 0 0
#> 23.2 16.92 1 61 0 0
#> 26 15.77 1 49 0 1
#> 107.1 11.18 1 54 1 0
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 17 24.00 0 38 0 1
#> 98 24.00 0 34 1 0
#> 12 24.00 0 63 0 0
#> 142 24.00 0 53 0 0
#> 33 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 21.1 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 75 24.00 0 21 1 0
#> 121.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 196 24.00 0 19 0 0
#> 147 24.00 0 76 1 0
#> 94.1 24.00 0 51 0 1
#> 46 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 38 24.00 0 31 1 0
#> 147.1 24.00 0 76 1 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 34.1 24.00 0 36 0 0
#> 38.1 24.00 0 31 1 0
#> 72.1 24.00 0 40 0 1
#> 2.1 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 64 24.00 0 43 0 0
#> 80 24.00 0 41 0 0
#> 193 24.00 0 45 0 1
#> 122 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 121.2 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 142.1 24.00 0 53 0 0
#> 143 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 163 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 84 24.00 0 39 0 1
#> 163.1 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 156 24.00 0 50 1 0
#> 115.1 24.00 0 NA 1 0
#> 95 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 102.1 24.00 0 49 0 0
#> 137 24.00 0 45 1 0
#> 47 24.00 0 38 0 1
#> 95.1 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 34.2 24.00 0 36 0 0
#> 151 24.00 0 42 0 0
#> 22 24.00 0 52 1 0
#> 83 24.00 0 6 0 0
#> 48.1 24.00 0 31 1 0
#> 48.2 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 161.1 24.00 0 45 0 0
#> 104 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 2.2 24.00 0 9 0 0
#> 95.2 24.00 0 68 0 1
#> 54 24.00 0 53 1 0
#> 122.1 24.00 0 66 0 0
#> 22.1 24.00 0 52 1 0
#> 65 24.00 0 57 1 0
#> 94.2 24.00 0 51 0 1
#> 80.1 24.00 0 41 0 0
#> 162.1 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 75.1 24.00 0 21 1 0
#> 98.1 24.00 0 34 1 0
#> 144 24.00 0 28 0 1
#> 7 24.00 0 37 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.647 NA NA NA
#> 2 age, Cure model 0.0120 NA NA NA
#> 3 grade_ii, Cure model 0.422 NA NA NA
#> 4 grade_iii, Cure model 0.482 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00528 NA NA NA
#> 2 grade_ii, Survival model 0.579 NA NA NA
#> 3 grade_iii, Survival model 0.290 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64728 0.01203 0.42228 0.48234
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 257.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.64728499 0.01202607 0.42228259 0.48233550
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00528232 0.57868746 0.29035147
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.70315126 0.80620726 0.35126567 0.98422285 0.13429116 0.83235308
#> [7] 0.42662970 0.96256144 0.61875050 0.72428290 0.75888407 0.16308947
#> [13] 0.97883696 0.28079728 0.76574781 0.35126567 0.84509416 0.31073270
#> [19] 0.65807170 0.94598796 0.44646184 0.57833839 0.68102692 0.46597099
#> [25] 0.88805447 0.56161006 0.83235308 0.74512225 0.37466895 0.65026763
#> [31] 0.71727619 0.73127056 0.10248435 0.67348523 0.46597099 0.23318140
#> [37] 0.98422285 0.29586901 0.88805447 0.59484099 0.59484099 0.78613494
#> [43] 0.94598796 0.19973596 0.44646184 0.42662970 0.04522162 0.86400321
#> [49] 0.56161006 0.50974240 0.37466895 0.24967519 0.98422285 0.80620726
#> [55] 0.54455529 0.33812975 0.81933087 0.91178038 0.96804123 0.93465225
#> [61] 0.84509416 0.86400321 0.19973596 0.04522162 0.62675261 0.78613494
#> [67] 0.96804123 0.37466895 0.95704637 0.40586200 0.46597099 0.70315126
#> [73] 0.68102692 0.76574781 0.91764915 0.51868996 0.41645764 0.77936596
#> [79] 0.91764915 0.85769621 0.86400321 0.62675261 0.46597099 0.58663484
#> [85] 0.53590983 0.91764915 0.74512225 0.86400321 0.62675261 0.24967519
#> [91] 0.54455529 0.94034046 0.16308947 0.73127056 0.81933087 0.51868996
#> [97] 0.46597099 0.69582297 0.31073270 0.90002471 0.78613494 0.59484099
#> [103] 0.66581111 0.90002471 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 29 140 153 25 168 37 166 149 181 157 13 129 77
#> 15.45 12.68 21.33 6.32 23.72 12.52 19.98 8.37 16.46 15.10 14.34 23.41 7.27
#> 63 81 153.1 42 194 188 183 105 40 39 55 43 108
#> 22.77 14.06 21.33 12.43 22.40 16.16 9.24 19.75 18.00 15.59 19.34 12.10 18.29
#> 37.1 133 32 79 18 180 78 125 58 92 25.1 169 43.1
#> 12.52 14.65 20.90 16.23 15.21 14.82 23.88 15.65 19.34 22.92 6.32 22.41 12.10
#> 23 23.1 14 183.1 69 105.1 166.1 24 49 108.1 76 32.1 113
#> 16.92 16.92 12.89 9.24 23.23 19.75 19.98 23.89 12.19 18.29 19.22 20.90 22.86
#> 25.2 140.1 8 197 177 159 70 101 42.1 49.1 69.1 24.1 85
#> 6.32 12.68 18.43 21.60 12.53 10.55 7.38 9.97 12.43 12.19 23.23 23.89 16.44
#> 14.1 70.1 32.2 16 150 55.1 29.1 39.1 81.1 145 97 158 60
#> 12.89 7.38 20.90 8.71 20.33 19.34 15.45 15.59 14.06 10.07 19.14 20.14 13.15
#> 145.1 56 49.2 85.1 55.2 45 179 145.2 133.1 49.3 85.2 113.1 8.1
#> 10.07 12.21 12.19 16.44 19.34 17.42 18.63 10.07 14.65 12.19 16.44 22.86 18.43
#> 187 129.1 180.1 177.1 97.1 55.3 167 194.1 107 14.2 23.2 26 107.1
#> 9.92 23.41 14.82 12.53 19.14 19.34 15.55 22.40 11.18 12.89 16.92 15.77 11.18
#> 121 94 34 21 72 17 98 12 142 33 12.1 21.1 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 121.1 53 102 2 196 147 94.1 46 82 38 147.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 174 34.1 38.1 72.1 2.1 178 64 80 193 122 109 121.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87 142.1 143 141 163 48 103 84 163.1 191 162 87.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 131 109.1 102.1 137 47 95.1 176 160 161 34.2 151 22
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 48.1 48.2 74 161.1 104 143.1 2.2 95.2 54 122.1 22.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.2 80.1 162.1 152 75.1 98.1 144 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[58]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.00453916 0.42833297 0.19671539
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.054371867 0.005840412 -0.543525783
#> grade_iii, Cure model
#> 0.319397815
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 194 22.40 1 38 0 1
#> 117 17.46 1 26 0 1
#> 106 16.67 1 49 1 0
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 86 23.81 1 58 0 1
#> 78 23.88 1 43 0 0
#> 13 14.34 1 54 0 1
#> 166 19.98 1 48 0 0
#> 88 18.37 1 47 0 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 89 11.44 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 154 12.63 1 20 1 0
#> 184 17.77 1 38 0 0
#> 145 10.07 1 65 1 0
#> 97 19.14 1 65 0 1
#> 145.1 10.07 1 65 1 0
#> 134 17.81 1 47 1 0
#> 155 13.08 1 26 0 0
#> 197 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 177 12.53 1 75 0 0
#> 6 15.64 1 39 0 0
#> 43.1 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 6.1 15.64 1 39 0 0
#> 93 10.33 1 52 0 1
#> 180 14.82 1 37 0 0
#> 66 22.13 1 53 0 0
#> 106.1 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 13.1 14.34 1 54 0 1
#> 60 13.15 1 38 1 0
#> 189 10.51 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 145.2 10.07 1 65 1 0
#> 55 19.34 1 69 0 1
#> 13.2 14.34 1 54 0 1
#> 157 15.10 1 47 0 0
#> 8 18.43 1 32 0 0
#> 194.1 22.40 1 38 0 1
#> 23 16.92 1 61 0 0
#> 43.2 12.10 1 61 0 1
#> 25 6.32 1 34 1 0
#> 69 23.23 1 25 0 1
#> 10 10.53 1 34 0 0
#> 29 15.45 1 68 1 0
#> 78.1 23.88 1 43 0 0
#> 45 17.42 1 54 0 1
#> 139 21.49 1 63 1 0
#> 92 22.92 1 47 0 1
#> 85.2 16.44 1 36 0 0
#> 123.1 13.00 1 44 1 0
#> 6.2 15.64 1 39 0 0
#> 130 16.47 1 53 0 1
#> 190 20.81 1 42 1 0
#> 159 10.55 1 50 0 1
#> 79 16.23 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 130.1 16.47 1 53 0 1
#> 113 22.86 1 34 0 0
#> 14 12.89 1 21 0 0
#> 10.1 10.53 1 34 0 0
#> 136 21.83 1 43 0 1
#> 125 15.65 1 67 1 0
#> 111 17.45 1 47 0 1
#> 168 23.72 1 70 0 0
#> 155.2 13.08 1 26 0 0
#> 39 15.59 1 37 0 1
#> 177.1 12.53 1 75 0 0
#> 89.1 11.44 1 NA 0 0
#> 32 20.90 1 37 1 0
#> 49.1 12.19 1 48 1 0
#> 89.2 11.44 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 190.1 20.81 1 42 1 0
#> 113.1 22.86 1 34 0 0
#> 66.1 22.13 1 53 0 0
#> 8.1 18.43 1 32 0 0
#> 79.1 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 155.3 13.08 1 26 0 0
#> 171 16.57 1 41 0 1
#> 43.3 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 58.1 19.34 1 39 0 0
#> 29.1 15.45 1 68 1 0
#> 100 16.07 1 60 0 0
#> 106.2 16.67 1 49 1 0
#> 14.1 12.89 1 21 0 0
#> 36 21.19 1 48 0 1
#> 41 18.02 1 40 1 0
#> 79.2 16.23 1 54 1 0
#> 39.1 15.59 1 37 0 1
#> 101 9.97 1 10 0 1
#> 105.1 19.75 1 60 0 0
#> 99.1 21.19 1 38 0 1
#> 13.3 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 89.3 11.44 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 190.2 20.81 1 42 1 0
#> 129 23.41 1 53 1 0
#> 105.2 19.75 1 60 0 0
#> 49.2 12.19 1 48 1 0
#> 101.1 9.97 1 10 0 1
#> 175 21.91 1 43 0 0
#> 13.4 14.34 1 54 0 1
#> 6.3 15.64 1 39 0 0
#> 98 24.00 0 34 1 0
#> 163 24.00 0 66 0 0
#> 53 24.00 0 32 0 1
#> 137 24.00 0 45 1 0
#> 137.1 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 17 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 46 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 103 24.00 0 56 1 0
#> 162 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 178 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 83 24.00 0 6 0 0
#> 83.1 24.00 0 6 0 0
#> 75.1 24.00 0 21 1 0
#> 28.1 24.00 0 67 1 0
#> 46.1 24.00 0 71 0 0
#> 173 24.00 0 19 0 1
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 178.1 24.00 0 52 1 0
#> 176 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 46.2 24.00 0 71 0 0
#> 198 24.00 0 66 0 1
#> 64.1 24.00 0 43 0 0
#> 160 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 103.1 24.00 0 56 1 0
#> 1 24.00 0 23 1 0
#> 185.1 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 62 24.00 0 71 0 0
#> 35 24.00 0 51 0 0
#> 178.2 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 9 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 62.1 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 64.2 24.00 0 43 0 0
#> 151 24.00 0 42 0 0
#> 196.1 24.00 0 19 0 0
#> 17.1 24.00 0 38 0 1
#> 198.1 24.00 0 66 0 1
#> 151.1 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 160.1 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 146.1 24.00 0 63 1 0
#> 80 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 144 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 126 24.00 0 48 0 0
#> 3 24.00 0 31 1 0
#> 185.2 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 137.2 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 53.1 24.00 0 32 0 1
#> 147.1 24.00 0 76 1 0
#> 65.1 24.00 0 57 1 0
#> 156.1 24.00 0 50 1 0
#> 193.1 24.00 0 45 0 1
#> 196.2 24.00 0 19 0 0
#> 200 24.00 0 64 0 0
#> 162.1 24.00 0 51 0 0
#> 132 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 173.1 24.00 0 19 0 1
#> 186.1 24.00 0 45 1 0
#> 87 24.00 0 27 0 0
#> 165 24.00 0 47 0 0
#> 193.2 24.00 0 45 0 1
#> 98.1 24.00 0 34 1 0
#> 131 24.00 0 66 0 0
#> 98.2 24.00 0 34 1 0
#> 87.1 24.00 0 27 0 0
#> 54 24.00 0 53 1 0
#> 151.2 24.00 0 42 0 0
#> 135.1 24.00 0 58 1 0
#> 27 24.00 0 63 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0544 NA NA NA
#> 2 age, Cure model 0.00584 NA NA NA
#> 3 grade_ii, Cure model -0.544 NA NA NA
#> 4 grade_iii, Cure model 0.319 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00454 NA NA NA
#> 2 grade_ii, Survival model 0.428 NA NA NA
#> 3 grade_iii, Survival model 0.197 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.05437 0.00584 -0.54353 0.31940
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.1
#> Residual Deviance: 258.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.054371867 0.005840412 -0.543525783 0.319397815
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.00453916 0.42833297 0.19671539
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.093888258 0.386409836 0.434505188 0.171408916 0.858405242 0.019103618
#> [7] 0.005665206 0.669839730 0.245041708 0.347807765 0.830241314 0.291241300
#> [13] 0.491167954 0.763745012 0.801695898 0.376778775 0.933949760 0.319123000
#> [19] 0.933949760 0.367186571 0.726069298 0.151541599 0.281770398 0.811205517
#> [25] 0.575398248 0.858405242 0.981056136 0.575398248 0.924396913 0.660265186
#> [31] 0.112315694 0.434505188 0.491167954 0.669839730 0.716517728 0.254300721
#> [37] 0.933949760 0.291241300 0.669839730 0.650712062 0.328728545 0.093888258
#> [43] 0.415262725 0.858405242 0.990542343 0.047513977 0.905397472 0.631799016
#> [49] 0.005665206 0.405636615 0.161521880 0.056799536 0.491167954 0.763745012
#> [55] 0.575398248 0.472193273 0.218490013 0.895876117 0.528469709 0.726069298
#> [61] 0.472193273 0.066113578 0.782699532 0.905397472 0.141480739 0.565910077
#> [67] 0.396021296 0.028143823 0.726069298 0.612813770 0.811205517 0.208930882
#> [73] 0.830241314 0.181185809 0.218490013 0.066113578 0.112315694 0.328728545
#> [79] 0.528469709 0.084128865 0.726069298 0.462625378 0.858405242 0.491167954
#> [85] 0.291241300 0.631799016 0.556400824 0.434505188 0.782699532 0.181185809
#> [91] 0.357533904 0.528469709 0.612813770 0.962193934 0.254300721 0.181185809
#> [97] 0.669839730 0.415262725 0.218490013 0.038074895 0.254300721 0.830241314
#> [103] 0.962193934 0.131419085 0.669839730 0.575398248 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 194 117 106 153 43 86 78 13 166 88 49 58 85
#> 22.40 17.46 16.67 21.33 12.10 23.81 23.88 14.34 19.98 18.37 12.19 19.34 16.44
#> 123 154 184 145 97 145.1 134 155 197 170 177 6 43.1
#> 13.00 12.63 17.77 10.07 19.14 10.07 17.81 13.08 21.60 19.54 12.53 15.64 12.10
#> 77 6.1 93 180 66 106.1 85.1 13.1 60 105 145.2 55 13.2
#> 7.27 15.64 10.33 14.82 22.13 16.67 16.44 14.34 13.15 19.75 10.07 19.34 14.34
#> 157 8 194.1 23 43.2 25 69 10 29 78.1 45 139 92
#> 15.10 18.43 22.40 16.92 12.10 6.32 23.23 10.53 15.45 23.88 17.42 21.49 22.92
#> 85.2 123.1 6.2 130 190 159 79 155.1 130.1 113 14 10.1 136
#> 16.44 13.00 15.64 16.47 20.81 10.55 16.23 13.08 16.47 22.86 12.89 10.53 21.83
#> 125 111 168 155.2 39 177.1 32 49.1 99 190.1 113.1 66.1 8.1
#> 15.65 17.45 23.72 13.08 15.59 12.53 20.90 12.19 21.19 20.81 22.86 22.13 18.43
#> 79.1 169 155.3 171 43.3 192 58.1 29.1 100 106.2 14.1 36 41
#> 16.23 22.41 13.08 16.57 12.10 16.44 19.34 15.45 16.07 16.67 12.89 21.19 18.02
#> 79.2 39.1 101 105.1 99.1 13.3 23.1 190.2 129 105.2 49.2 101.1 175
#> 16.23 15.59 9.97 19.75 21.19 14.34 16.92 20.81 23.41 19.75 12.19 9.97 21.91
#> 13.4 6.3 98 163 53 137 137.1 135 17 28 46 75 103
#> 14.34 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162 146 178 196 83 83.1 75.1 28.1 46.1 173 152 185 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 64 46.2 198 64.1 160 120 103.1 1 185.1 62 35 178.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 47 9 186 65 62.1 11 64.2 151 196.1 17.1 198.1 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 160.1 146.1 80 12 144 147 126 3 185.2 156 137.2 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 147.1 65.1 156.1 193.1 196.2 200 162.1 132 172 173.1 186.1 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 193.2 98.1 131 98.2 87.1 54 151.2 135.1 27
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[59]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01362911 0.61496888 0.48713488
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.49191820 0.02336552 0.49570430
#> grade_iii, Cure model
#> 1.14389770
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 133 14.65 1 57 0 0
#> 124 9.73 1 NA 1 0
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 157 15.10 1 47 0 0
#> 40 18.00 1 28 1 0
#> 89 11.44 1 NA 0 0
#> 97 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 128.1 20.35 1 35 0 1
#> 45 17.42 1 54 0 1
#> 140 12.68 1 59 1 0
#> 166.1 19.98 1 48 0 0
#> 117 17.46 1 26 0 1
#> 60 13.15 1 38 1 0
#> 190 20.81 1 42 1 0
#> 157.1 15.10 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 110.1 17.56 1 65 0 1
#> 158 20.14 1 74 1 0
#> 43 12.10 1 61 0 1
#> 37 12.52 1 57 1 0
#> 61 10.12 1 36 0 1
#> 153 21.33 1 55 1 0
#> 97.1 19.14 1 65 0 1
#> 81 14.06 1 34 0 0
#> 77 7.27 1 67 0 1
#> 175 21.91 1 43 0 0
#> 166.2 19.98 1 48 0 0
#> 171 16.57 1 41 0 1
#> 78 23.88 1 43 0 0
#> 91 5.33 1 61 0 1
#> 134 17.81 1 47 1 0
#> 170 19.54 1 43 0 1
#> 79 16.23 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 159 10.55 1 50 0 1
#> 184 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 15 22.68 1 48 0 0
#> 5 16.43 1 51 0 1
#> 181 16.46 1 45 0 1
#> 157.2 15.10 1 47 0 0
#> 179.1 18.63 1 42 0 0
#> 171.1 16.57 1 41 0 1
#> 63 22.77 1 31 1 0
#> 91.1 5.33 1 61 0 1
#> 15.1 22.68 1 48 0 0
#> 37.1 12.52 1 57 1 0
#> 4 17.64 1 NA 0 1
#> 92.1 22.92 1 47 0 1
#> 4.1 17.64 1 NA 0 1
#> 85 16.44 1 36 0 0
#> 150 20.33 1 48 0 0
#> 128.2 20.35 1 35 0 1
#> 91.2 5.33 1 61 0 1
#> 128.3 20.35 1 35 0 1
#> 88 18.37 1 47 0 0
#> 61.1 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 195 11.76 1 NA 1 0
#> 77.1 7.27 1 67 0 1
#> 13.2 14.34 1 54 0 1
#> 58 19.34 1 39 0 0
#> 197 21.60 1 69 1 0
#> 40.1 18.00 1 28 1 0
#> 111 17.45 1 47 0 1
#> 57 14.46 1 45 0 1
#> 158.1 20.14 1 74 1 0
#> 49 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 164 23.60 1 76 0 1
#> 97.2 19.14 1 65 0 1
#> 25 6.32 1 34 1 0
#> 77.2 7.27 1 67 0 1
#> 90 20.94 1 50 0 1
#> 167 15.55 1 56 1 0
#> 76 19.22 1 54 0 1
#> 15.2 22.68 1 48 0 0
#> 179.2 18.63 1 42 0 0
#> 149 8.37 1 33 1 0
#> 164.1 23.60 1 76 0 1
#> 187 9.92 1 39 1 0
#> 159.1 10.55 1 50 0 1
#> 57.1 14.46 1 45 0 1
#> 164.2 23.60 1 76 0 1
#> 15.3 22.68 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 106 16.67 1 49 1 0
#> 159.2 10.55 1 50 0 1
#> 25.1 6.32 1 34 1 0
#> 159.3 10.55 1 50 0 1
#> 45.1 17.42 1 54 0 1
#> 93 10.33 1 52 0 1
#> 97.3 19.14 1 65 0 1
#> 50.1 10.02 1 NA 1 0
#> 106.1 16.67 1 49 1 0
#> 79.1 16.23 1 54 1 0
#> 55 19.34 1 69 0 1
#> 139 21.49 1 63 1 0
#> 145 10.07 1 65 1 0
#> 154 12.63 1 20 1 0
#> 42 12.43 1 49 0 1
#> 183 9.24 1 67 1 0
#> 36 21.19 1 48 0 1
#> 39 15.59 1 37 0 1
#> 129 23.41 1 53 1 0
#> 123 13.00 1 44 1 0
#> 157.3 15.10 1 47 0 0
#> 53 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 156 24.00 0 50 1 0
#> 2 24.00 0 9 0 0
#> 178 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 54 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 2.1 24.00 0 9 0 0
#> 102.1 24.00 0 49 0 0
#> 7 24.00 0 37 1 0
#> 53.1 24.00 0 32 0 1
#> 112 24.00 0 61 0 0
#> 198.1 24.00 0 66 0 1
#> 35 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 94 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 34 24.00 0 36 0 0
#> 73 24.00 0 NA 0 1
#> 11 24.00 0 42 0 1
#> 152 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 165 24.00 0 47 0 0
#> 132 24.00 0 55 0 0
#> 109 24.00 0 48 0 0
#> 156.1 24.00 0 50 1 0
#> 53.2 24.00 0 32 0 1
#> 72 24.00 0 40 0 1
#> 33.1 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 156.2 24.00 0 50 1 0
#> 35.1 24.00 0 51 0 0
#> 35.2 24.00 0 51 0 0
#> 33.2 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 109.1 24.00 0 48 0 0
#> 2.2 24.00 0 9 0 0
#> 122 24.00 0 66 0 0
#> 3.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 72.1 24.00 0 40 0 1
#> 11.1 24.00 0 42 0 1
#> 186 24.00 0 45 1 0
#> 119 24.00 0 17 0 0
#> 9 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 186.1 24.00 0 45 1 0
#> 122.1 24.00 0 66 0 0
#> 161.1 24.00 0 45 0 0
#> 21 24.00 0 47 0 0
#> 11.2 24.00 0 42 0 1
#> 198.2 24.00 0 66 0 1
#> 135 24.00 0 58 1 0
#> 3.2 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 44 24.00 0 56 0 0
#> 1 24.00 0 23 1 0
#> 75 24.00 0 21 1 0
#> 120 24.00 0 68 0 1
#> 9.1 24.00 0 31 1 0
#> 172.1 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 72.2 24.00 0 40 0 1
#> 71 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 120.1 24.00 0 68 0 1
#> 53.3 24.00 0 32 0 1
#> 73.1 24.00 0 NA 0 1
#> 143.1 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 54.1 24.00 0 53 1 0
#> 174 24.00 0 49 1 0
#> 138 24.00 0 44 1 0
#> 38 24.00 0 31 1 0
#> 9.2 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 135.1 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 131 24.00 0 66 0 0
#> 138.1 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 75.1 24.00 0 21 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.49 NA NA NA
#> 2 age, Cure model 0.0234 NA NA NA
#> 3 grade_ii, Cure model 0.496 NA NA NA
#> 4 grade_iii, Cure model 1.14 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0136 NA NA NA
#> 2 grade_ii, Survival model 0.615 NA NA NA
#> 3 grade_iii, Survival model 0.487 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.49192 0.02337 0.49570 1.14390
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 244.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.49191820 0.02336552 0.49570430 1.14389770
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01362911 0.61496888 0.48713488
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.6164061115 0.6164061115 0.5826771143 0.2719225494 0.1660897273
#> [6] 0.5392872177 0.3112168663 0.2354975194 0.1136704782 0.1136704782
#> [11] 0.3920638026 0.6847232740 0.1660897273 0.3714538001 0.6617041296
#> [16] 0.1057495117 0.5392872177 0.3510892655 0.3510892655 0.1500974422
#> [21] 0.7536811903 0.7077286742 0.8346253841 0.0822391751 0.2354975194
#> [26] 0.6501726022 0.9052320193 0.0598787920 0.1660897273 0.4333449657
#> [31] 0.0006784223 0.9643313284 0.3309337901 0.1911925688 0.4858653776
#> [36] 0.1911925688 0.7769124242 0.3409513181 0.0207557451 0.0367530884
#> [41] 0.4752096750 0.4540807865 0.5392872177 0.2719225494 0.4333449657
#> [46] 0.0312089865 0.9643313284 0.0367530884 0.7077286742 0.0207557451
#> [51] 0.4645986527 0.1421598188 0.1136704782 0.9643313284 0.1136704782
#> [56] 0.3010248580 0.8346253841 0.5070479471 0.9052320193 0.6164061115
#> [61] 0.2084638139 0.0671270924 0.3112168663 0.3817390096 0.5939581307
#> [66] 0.1500974422 0.7421274388 0.7652867593 0.0040914291 0.2354975194
#> [71] 0.9406598458 0.9052320193 0.0978029663 0.5285194300 0.2263098263
#> [76] 0.0367530884 0.2719225494 0.8934276989 0.0040914291 0.8698037029
#> [81] 0.7769124242 0.5939581307 0.0040914291 0.0367530884 0.4126777066
#> [86] 0.7769124242 0.9406598458 0.7769124242 0.3920638026 0.8228571867
#> [91] 0.2354975194 0.4126777066 0.4858653776 0.2084638139 0.0746001355
#> [96] 0.8579981853 0.6962647660 0.7305806062 0.8815952975 0.0899691161
#> [101] 0.5177817930 0.0151671529 0.6732152151 0.5392872177 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 13 13.1 133 179 166 157 40 97 128 128.1 45 140 166.1
#> 14.34 14.34 14.65 18.63 19.98 15.10 18.00 19.14 20.35 20.35 17.42 12.68 19.98
#> 117 60 190 157.1 110 110.1 158 43 37 61 153 97.1 81
#> 17.46 13.15 20.81 15.10 17.56 17.56 20.14 12.10 12.52 10.12 21.33 19.14 14.06
#> 77 175 166.2 171 78 91 134 170 79 170.1 159 184 92
#> 7.27 21.91 19.98 16.57 23.88 5.33 17.81 19.54 16.23 19.54 10.55 17.77 22.92
#> 15 5 181 157.2 179.1 171.1 63 91.1 15.1 37.1 92.1 85 150
#> 22.68 16.43 16.46 15.10 18.63 16.57 22.77 5.33 22.68 12.52 22.92 16.44 20.33
#> 128.2 91.2 128.3 88 61.1 188 77.1 13.2 58 197 40.1 111 57
#> 20.35 5.33 20.35 18.37 10.12 16.16 7.27 14.34 19.34 21.60 18.00 17.45 14.46
#> 158.1 49 107 164 97.2 25 77.2 90 167 76 15.2 179.2 149
#> 20.14 12.19 11.18 23.60 19.14 6.32 7.27 20.94 15.55 19.22 22.68 18.63 8.37
#> 164.1 187 159.1 57.1 164.2 15.3 106 159.2 25.1 159.3 45.1 93 97.3
#> 23.60 9.92 10.55 14.46 23.60 22.68 16.67 10.55 6.32 10.55 17.42 10.33 19.14
#> 106.1 79.1 55 139 145 154 42 183 36 39 129 123 157.3
#> 16.67 16.23 19.34 21.49 10.07 12.63 12.43 9.24 21.19 15.59 23.41 13.00 15.10
#> 53 198 191 162 102 156 2 178 161 54 33 2.1 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 53.1 112 198.1 35 143 94 116 34 11 152 82 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 109 156.1 53.2 72 33.1 22 156.2 35.1 35.2 33.2 3 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 2.2 122 3.1 87 72.1 11.1 186 119 9 95 186.1 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 21 11.2 198.2 135 3.2 172 44 1 75 120 9.1 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83 72.2 71 34.1 120.1 53.3 143.1 116.1 54.1 174 138 38 9.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 135.1 151 131 138.1 65 19 75.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[60]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01752395 0.75141712 0.60046092
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.310480985 0.001378216 -0.052249641
#> grade_iii, Cure model
#> 1.423456921
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 42 12.43 1 49 0 1
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 188 16.16 1 46 0 1
#> 96 14.54 1 33 0 1
#> 150 20.33 1 48 0 0
#> 168 23.72 1 70 0 0
#> 187 9.92 1 39 1 0
#> 14 12.89 1 21 0 0
#> 61 10.12 1 36 0 1
#> 26 15.77 1 49 0 1
#> 78 23.88 1 43 0 0
#> 129 23.41 1 53 1 0
#> 13 14.34 1 54 0 1
#> 171 16.57 1 41 0 1
#> 77 7.27 1 67 0 1
#> 195 11.76 1 NA 1 0
#> 51 18.23 1 83 0 1
#> 97 19.14 1 65 0 1
#> 6 15.64 1 39 0 0
#> 181 16.46 1 45 0 1
#> 154 12.63 1 20 1 0
#> 6.1 15.64 1 39 0 0
#> 153 21.33 1 55 1 0
#> 190 20.81 1 42 1 0
#> 189 10.51 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 195.1 11.76 1 NA 1 0
#> 43 12.10 1 61 0 1
#> 23 16.92 1 61 0 0
#> 125 15.65 1 67 1 0
#> 180 14.82 1 37 0 0
#> 57 14.46 1 45 0 1
#> 99 21.19 1 38 0 1
#> 129.1 23.41 1 53 1 0
#> 128 20.35 1 35 0 1
#> 130.1 16.47 1 53 0 1
#> 159 10.55 1 50 0 1
#> 4 17.64 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 145 10.07 1 65 1 0
#> 123 13.00 1 44 1 0
#> 90 20.94 1 50 0 1
#> 171.1 16.57 1 41 0 1
#> 111 17.45 1 47 0 1
#> 153.1 21.33 1 55 1 0
#> 159.1 10.55 1 50 0 1
#> 89 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 164 23.60 1 76 0 1
#> 169 22.41 1 46 0 0
#> 97.1 19.14 1 65 0 1
#> 100 16.07 1 60 0 0
#> 139 21.49 1 63 1 0
#> 164.1 23.60 1 76 0 1
#> 188.1 16.16 1 46 0 1
#> 79 16.23 1 54 1 0
#> 125.1 15.65 1 67 1 0
#> 181.1 16.46 1 45 0 1
#> 157 15.10 1 47 0 0
#> 69 23.23 1 25 0 1
#> 159.2 10.55 1 50 0 1
#> 60 13.15 1 38 1 0
#> 155 13.08 1 26 0 0
#> 60.1 13.15 1 38 1 0
#> 100.1 16.07 1 60 0 0
#> 58 19.34 1 39 0 0
#> 90.1 20.94 1 50 0 1
#> 60.2 13.15 1 38 1 0
#> 190.1 20.81 1 42 1 0
#> 93 10.33 1 52 0 1
#> 181.2 16.46 1 45 0 1
#> 195.2 11.76 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 15 22.68 1 48 0 0
#> 30 17.43 1 78 0 0
#> 15.1 22.68 1 48 0 0
#> 79.1 16.23 1 54 1 0
#> 58.1 19.34 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 90.2 20.94 1 50 0 1
#> 154.1 12.63 1 20 1 0
#> 169.1 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 40 18.00 1 28 1 0
#> 86 23.81 1 58 0 1
#> 107.1 11.18 1 54 1 0
#> 26.1 15.77 1 49 0 1
#> 105 19.75 1 60 0 0
#> 85 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 181.3 16.46 1 45 0 1
#> 13.1 14.34 1 54 0 1
#> 76 19.22 1 54 0 1
#> 189.1 10.51 1 NA 1 0
#> 107.2 11.18 1 54 1 0
#> 45 17.42 1 54 0 1
#> 197 21.60 1 69 1 0
#> 164.2 23.60 1 76 0 1
#> 164.3 23.60 1 76 0 1
#> 86.1 23.81 1 58 0 1
#> 127 3.53 1 62 0 1
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 6.2 15.64 1 39 0 0
#> 61.1 10.12 1 36 0 1
#> 169.2 22.41 1 46 0 0
#> 78.1 23.88 1 43 0 0
#> 61.2 10.12 1 36 0 1
#> 56.1 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 127.1 3.53 1 62 0 1
#> 178 24.00 0 52 1 0
#> 11 24.00 0 42 0 1
#> 161 24.00 0 45 0 0
#> 163 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 38 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 161.1 24.00 0 45 0 0
#> 142 24.00 0 53 0 0
#> 35 24.00 0 51 0 0
#> 148 24.00 0 61 1 0
#> 74 24.00 0 43 0 1
#> 48 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 35.1 24.00 0 51 0 0
#> 174 24.00 0 49 1 0
#> 53 24.00 0 32 0 1
#> 35.2 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 191 24.00 0 60 0 1
#> 162 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 82 24.00 0 34 0 0
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#> 64 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 132 24.00 0 55 0 0
#> 75 24.00 0 21 1 0
#> 193 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 116 24.00 0 58 0 1
#> 21 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 9 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 138 24.00 0 44 1 0
#> 142.1 24.00 0 53 0 0
#> 141 24.00 0 44 1 0
#> 71.1 24.00 0 51 0 0
#> 161.2 24.00 0 45 0 0
#> 112 24.00 0 61 0 0
#> 161.3 24.00 0 45 0 0
#> 54 24.00 0 53 1 0
#> 35.3 24.00 0 51 0 0
#> 44 24.00 0 56 0 0
#> 54.1 24.00 0 53 1 0
#> 44.1 24.00 0 56 0 0
#> 33 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 141.1 24.00 0 44 1 0
#> 163.1 24.00 0 66 0 0
#> 71.2 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 31 24.00 0 36 0 1
#> 87 24.00 0 27 0 0
#> 34 24.00 0 36 0 0
#> 54.2 24.00 0 53 1 0
#> 104.1 24.00 0 50 1 0
#> 115 24.00 0 NA 1 0
#> 121 24.00 0 57 1 0
#> 156.1 24.00 0 50 1 0
#> 20 24.00 0 46 1 0
#> 178.2 24.00 0 52 1 0
#> 44.2 24.00 0 56 0 0
#> 172 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 75.1 24.00 0 21 1 0
#> 162.1 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 112.2 24.00 0 61 0 0
#> 17 24.00 0 38 0 1
#> 17.1 24.00 0 38 0 1
#> 48.1 24.00 0 31 1 0
#> 135 24.00 0 58 1 0
#> 172.1 24.00 0 41 0 0
#> 82.1 24.00 0 34 0 0
#> 74.1 24.00 0 43 0 1
#> 161.4 24.00 0 45 0 0
#> 98 24.00 0 34 1 0
#> 95.1 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.310 NA NA NA
#> 2 age, Cure model 0.00138 NA NA NA
#> 3 grade_ii, Cure model -0.0522 NA NA NA
#> 4 grade_iii, Cure model 1.42 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0175 NA NA NA
#> 2 grade_ii, Survival model 0.751 NA NA NA
#> 3 grade_iii, Survival model 0.600 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.310481 0.001378 -0.052250 1.423457
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 243.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.310480985 0.001378216 -0.052249641 1.423456921
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01752395 0.75141712 0.60046092
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.7161693944 0.8554880718 0.3143280298 0.4074252204 0.5683461560
#> [6] 0.1738075094 0.0085082808 0.9468189687 0.6791480649 0.8946566590
#> [11] 0.4512621279 0.0010469274 0.0262619899 0.5929684594 0.2942087815
#> [16] 0.9600300721 0.2356634757 0.2172825483 0.4967101346 0.3348145825
#> [21] 0.6917092266 0.4967101346 0.0967265976 0.1499238587 0.0402676784
#> [26] 0.7663438202 0.2840500062 0.4737982267 0.5560514406 0.5806349225
#> [31] 0.1116428087 0.0262619899 0.1657111788 0.3143280298 0.8170800042
#> [36] 0.7791023927 0.9335948883 0.6666580320 0.1268432340 0.2942087815
#> [41] 0.2547456318 0.0967265976 0.8170800042 0.0001495085 0.0117869450
#> [46] 0.0563002237 0.2172825483 0.4289794450 0.0891903848 0.0117869450
#> [51] 0.4074252204 0.3860810942 0.4737982267 0.3348145825 0.5438850773
#> [56] 0.0354479857 0.8170800042 0.6176764852 0.6541725543 0.6176764852
#> [61] 0.4289794450 0.1906956036 0.1268432340 0.6176764852 0.1499238587
#> [66] 0.8685402668 0.3348145825 0.1116428087 0.0453614745 0.2643026705
#> [71] 0.0453614745 0.3860810942 0.1906956036 0.8685402668 0.1268432340
#> [76] 0.6917092266 0.0563002237 0.5318695479 0.2452598064 0.0041380806
#> [81] 0.7791023927 0.4512621279 0.1821242246 0.3753638551 0.7285542803
#> [86] 0.3348145825 0.5929684594 0.2082159092 0.7791023927 0.2741243373
#> [91] 0.0818389953 0.0117869450 0.0117869450 0.0041380806 0.9733210180
#> [96] 0.0747226540 0.4967101346 0.8946566590 0.0563002237 0.0010469274
#> [101] 0.8946566590 0.7285542803 0.7536642140 0.9733210180 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 42 52 130 188 96 150 168 187 14 61 26 78 129
#> 12.43 10.42 16.47 16.16 14.54 20.33 23.72 9.92 12.89 10.12 15.77 23.88 23.41
#> 13 171 77 51 97 6 181 154 6.1 153 190 113 43
#> 14.34 16.57 7.27 18.23 19.14 15.64 16.46 12.63 15.64 21.33 20.81 22.86 12.10
#> 23 125 180 57 99 129.1 128 130.1 159 107 145 123 90
#> 16.92 15.65 14.82 14.46 21.19 23.41 20.35 16.47 10.55 11.18 10.07 13.00 20.94
#> 171.1 111 153.1 159.1 24 164 169 97.1 100 139 164.1 188.1 79
#> 16.57 17.45 21.33 10.55 23.89 23.60 22.41 19.14 16.07 21.49 23.60 16.16 16.23
#> 125.1 181.1 157 69 159.2 60 155 60.1 100.1 58 90.1 60.2 190.1
#> 15.65 16.46 15.10 23.23 10.55 13.15 13.08 13.15 16.07 19.34 20.94 13.15 20.81
#> 93 181.2 36 15 30 15.1 79.1 58.1 93.1 90.2 154.1 169.1 18
#> 10.33 16.46 21.19 22.68 17.43 22.68 16.23 19.34 10.33 20.94 12.63 22.41 15.21
#> 40 86 107.1 26.1 105 85 56 181.3 13.1 76 107.2 45 197
#> 18.00 23.81 11.18 15.77 19.75 16.44 12.21 16.46 14.34 19.22 11.18 17.42 21.60
#> 164.2 164.3 86.1 127 66 6.2 61.1 169.2 78.1 61.2 56.1 49 127.1
#> 23.60 23.60 23.81 3.53 22.13 15.64 10.12 22.41 23.88 10.12 12.21 12.19 3.53
#> 178 11 161 163 160 95 38 103 161.1 142 35 148 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 12 35.1 174 53 35.2 146 62 191 162 156 82 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 104 147 64 28 65 132 75 193 1 116 21 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 196 9 178.1 138 142.1 141 71.1 161.2 112 161.3 54 35.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 54.1 44.1 33 186 141.1 163.1 71.2 112.1 31 87 34 54.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.1 121 156.1 20 178.2 44.2 172 198 75.1 162.1 176 112.2 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 48.1 135 172.1 82.1 74.1 161.4 98 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[61]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01178958 0.72754922 0.40220229
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.1696090614 -0.0004442169 0.1520762957
#> grade_iii, Cure model
#> 1.0519062962
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 63 22.77 1 31 1 0
#> 57 14.46 1 45 0 1
#> 171 16.57 1 41 0 1
#> 188 16.16 1 46 0 1
#> 96 14.54 1 33 0 1
#> 181 16.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 59 10.16 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 199 19.81 1 NA 0 1
#> 101 9.97 1 10 0 1
#> 184 17.77 1 38 0 0
#> 171.1 16.57 1 41 0 1
#> 49 12.19 1 48 1 0
#> 167 15.55 1 56 1 0
#> 128 20.35 1 35 0 1
#> 128.1 20.35 1 35 0 1
#> 134.1 17.81 1 47 1 0
#> 39 15.59 1 37 0 1
#> 8 18.43 1 32 0 0
#> 88 18.37 1 47 0 0
#> 105 19.75 1 60 0 0
#> 5 16.43 1 51 0 1
#> 127 3.53 1 62 0 1
#> 128.2 20.35 1 35 0 1
#> 197 21.60 1 69 1 0
#> 150 20.33 1 48 0 0
#> 113 22.86 1 34 0 0
#> 199.1 19.81 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 123 13.00 1 44 1 0
#> 50 10.02 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 86 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 177.1 12.53 1 75 0 0
#> 127.1 3.53 1 62 0 1
#> 76 19.22 1 54 0 1
#> 85 16.44 1 36 0 0
#> 133 14.65 1 57 0 0
#> 50.1 10.02 1 NA 1 0
#> 179.1 18.63 1 42 0 0
#> 86.1 23.81 1 58 0 1
#> 108 18.29 1 39 0 1
#> 55 19.34 1 69 0 1
#> 117 17.46 1 26 0 1
#> 195 11.76 1 NA 1 0
#> 23 16.92 1 61 0 0
#> 58 19.34 1 39 0 0
#> 194 22.40 1 38 0 1
#> 136 21.83 1 43 0 1
#> 169 22.41 1 46 0 0
#> 159 10.55 1 50 0 1
#> 184.2 17.77 1 38 0 0
#> 49.1 12.19 1 48 1 0
#> 99 21.19 1 38 0 1
#> 60 13.15 1 38 1 0
#> 88.1 18.37 1 47 0 0
#> 117.1 17.46 1 26 0 1
#> 16 8.71 1 71 0 1
#> 92 22.92 1 47 0 1
#> 123.1 13.00 1 44 1 0
#> 145 10.07 1 65 1 0
#> 43 12.10 1 61 0 1
#> 136.1 21.83 1 43 0 1
#> 79 16.23 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 108.1 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 105.1 19.75 1 60 0 0
#> 192 16.44 1 31 1 0
#> 57.1 14.46 1 45 0 1
#> 90 20.94 1 50 0 1
#> 168 23.72 1 70 0 0
#> 167.1 15.55 1 56 1 0
#> 188.1 16.16 1 46 0 1
#> 77 7.27 1 67 0 1
#> 125 15.65 1 67 1 0
#> 45 17.42 1 54 0 1
#> 99.1 21.19 1 38 0 1
#> 108.2 18.29 1 39 0 1
#> 36 21.19 1 48 0 1
#> 195.1 11.76 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 63.1 22.77 1 31 1 0
#> 113.1 22.86 1 34 0 0
#> 105.2 19.75 1 60 0 0
#> 66 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 92.1 22.92 1 47 0 1
#> 41 18.02 1 40 1 0
#> 150.1 20.33 1 48 0 0
#> 50.2 10.02 1 NA 1 0
#> 124 9.73 1 NA 1 0
#> 43.1 12.10 1 61 0 1
#> 24.1 23.89 1 38 0 0
#> 30 17.43 1 78 0 0
#> 170 19.54 1 43 0 1
#> 24.2 23.89 1 38 0 0
#> 68 20.62 1 44 0 0
#> 15 22.68 1 48 0 0
#> 139 21.49 1 63 1 0
#> 30.1 17.43 1 78 0 0
#> 107 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 100 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 92.2 22.92 1 47 0 1
#> 96.1 14.54 1 33 0 1
#> 133.1 14.65 1 57 0 0
#> 112 24.00 0 61 0 0
#> 72 24.00 0 40 0 1
#> 122 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 53 24.00 0 32 0 1
#> 173 24.00 0 19 0 1
#> 48 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 132 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 172.1 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 172.2 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 186 24.00 0 45 1 0
#> 34 24.00 0 36 0 0
#> 71 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 135 24.00 0 58 1 0
#> 151 24.00 0 42 0 0
#> 151.1 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 46.1 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 7 24.00 0 37 1 0
#> 98 24.00 0 34 1 0
#> 103 24.00 0 56 1 0
#> 147 24.00 0 76 1 0
#> 120 24.00 0 68 0 1
#> 144 24.00 0 28 0 1
#> 12 24.00 0 63 0 0
#> 151.2 24.00 0 42 0 0
#> 7.1 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 165 24.00 0 47 0 0
#> 198 24.00 0 66 0 1
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 103.1 24.00 0 56 1 0
#> 1 24.00 0 23 1 0
#> 74 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 162 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 17.1 24.00 0 38 0 1
#> 95.1 24.00 0 68 0 1
#> 112.1 24.00 0 61 0 0
#> 161 24.00 0 45 0 0
#> 178.1 24.00 0 52 1 0
#> 44 24.00 0 56 0 0
#> 200 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 20 24.00 0 46 1 0
#> 73.1 24.00 0 NA 0 1
#> 35 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 21.2 24.00 0 47 0 0
#> 62.1 24.00 0 71 0 0
#> 172.3 24.00 0 41 0 0
#> 62.2 24.00 0 71 0 0
#> 17.2 24.00 0 38 0 1
#> 62.3 24.00 0 71 0 0
#> 152.2 24.00 0 36 0 1
#> 98.1 24.00 0 34 1 0
#> 20.1 24.00 0 46 1 0
#> 2 24.00 0 9 0 0
#> 62.4 24.00 0 71 0 0
#> 64 24.00 0 43 0 0
#> 126 24.00 0 48 0 0
#> 28 24.00 0 67 1 0
#> 156 24.00 0 50 1 0
#> 151.3 24.00 0 42 0 0
#> 20.2 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 95.2 24.00 0 68 0 1
#> 141.1 24.00 0 44 1 0
#> 98.2 24.00 0 34 1 0
#> 73.2 24.00 0 NA 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.170 NA NA NA
#> 2 age, Cure model -0.000444 NA NA NA
#> 3 grade_ii, Cure model 0.152 NA NA NA
#> 4 grade_iii, Cure model 1.05 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0118 NA NA NA
#> 2 grade_ii, Survival model 0.728 NA NA NA
#> 3 grade_iii, Survival model 0.402 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1696091 -0.0004442 0.1520763 1.0519063
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.1696090614 -0.0004442169 0.1520762957 1.0519062962
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01178958 0.72754922 0.40220229
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.5670562 0.4036704 0.9161275 0.8131214 0.8503280 0.9073095 0.8239725
#> [8] 0.7429903 0.6253308 0.9736465 0.7551032 0.8131214 0.9458321 0.8846961
#> [15] 0.5846720 0.5846720 0.7429903 0.8799481 0.6971322 0.7039623 0.6330530
#> [22] 0.8399317 0.9926470 0.5846720 0.5088949 0.6091993 0.3709969 0.6834781
#> [29] 0.9291259 0.7551032 0.2460438 0.9375319 0.9375319 0.9926470 0.6765272
#> [36] 0.8293612 0.8983869 0.6834781 0.2460438 0.7173645 0.6624337 0.7729577
#> [43] 0.8019176 0.6624337 0.4594462 0.4854020 0.4457906 0.9658620 0.7551032
#> [50] 0.9458321 0.5300677 0.9248166 0.7039623 0.7729577 0.9851306 0.3209643
#> [57] 0.9291259 0.9697812 0.9539440 0.4854020 0.8451764 0.9736465 0.7173645
#> [64] 0.1298795 0.6330530 0.8293612 0.9161275 0.5578873 0.2970283 0.8846961
#> [71] 0.8503280 0.9889052 0.8704103 0.7962212 0.5300677 0.7173645 0.5300677
#> [78] 0.8654335 0.8938714 0.4036704 0.3709969 0.6330530 0.4725787 0.8075717
#> [85] 0.3209643 0.7366383 0.6091993 0.9539440 0.1298795 0.7847194 0.6551177
#> [92] 0.1298795 0.5759099 0.4318272 0.5198420 0.7847194 0.9619156 0.9813202
#> [99] 0.8604087 0.8704103 0.3209643 0.9073095 0.8983869 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#>
#> $Time
#> 32 63 57 171 188 96 181 134 158 101 184 171.1 49
#> 20.90 22.77 14.46 16.57 16.16 14.54 16.46 17.81 20.14 9.97 17.77 16.57 12.19
#> 167 128 128.1 134.1 39 8 88 105 5 127 128.2 197 150
#> 15.55 20.35 20.35 17.81 15.59 18.43 18.37 19.75 16.43 3.53 20.35 21.60 20.33
#> 113 179 123 184.1 86 177 177.1 127.1 76 85 133 179.1 86.1
#> 22.86 18.63 13.00 17.77 23.81 12.53 12.53 3.53 19.22 16.44 14.65 18.63 23.81
#> 108 55 117 23 58 194 136 169 159 184.2 49.1 99 60
#> 18.29 19.34 17.46 16.92 19.34 22.40 21.83 22.41 10.55 17.77 12.19 21.19 13.15
#> 88.1 117.1 16 92 123.1 145 43 136.1 79 101.1 108.1 24 105.1
#> 18.37 17.46 8.71 22.92 13.00 10.07 12.10 21.83 16.23 9.97 18.29 23.89 19.75
#> 192 57.1 90 168 167.1 188.1 77 125 45 99.1 108.2 36 26
#> 16.44 14.46 20.94 23.72 15.55 16.16 7.27 15.65 17.42 21.19 18.29 21.19 15.77
#> 29 63.1 113.1 105.2 66 106 92.1 41 150.1 43.1 24.1 30 170
#> 15.45 22.77 22.86 19.75 22.13 16.67 22.92 18.02 20.33 12.10 23.89 17.43 19.54
#> 24.2 68 15 139 30.1 107 187 100 125.1 92.2 96.1 133.1 112
#> 23.89 20.62 22.68 21.49 17.43 11.18 9.92 16.07 15.65 22.92 14.54 14.65 24.00
#> 72 122 191 53 173 48 109 132 172 178 172.1 152 172.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 186 34 71 152.1 185 122.1 65 22 135 151 151.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 95 7 98 103 147 120 144 12 151.2 7.1 165 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174 116 103.1 1 74 31 54 87 162 62 17 141 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 112.1 161 178.1 44 200 165.1 21.1 20 35 143 21.2 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.3 62.2 17.2 62.3 152.2 98.1 20.1 2 62.4 64 126 28 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.3 20.2 163 95.2 141.1 98.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[62]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01040954 0.71188538 0.72607319
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.18084089 0.02159535 -0.02290019
#> grade_iii, Cure model
#> 1.23446255
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 149 8.37 1 33 1 0
#> 113 22.86 1 34 0 0
#> 199 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 108 18.29 1 39 0 1
#> 91 5.33 1 61 0 1
#> 25 6.32 1 34 1 0
#> 26 15.77 1 49 0 1
#> 114 13.68 1 NA 0 0
#> 92 22.92 1 47 0 1
#> 106 16.67 1 49 1 0
#> 89 11.44 1 NA 0 0
#> 24 23.89 1 38 0 0
#> 93 10.33 1 52 0 1
#> 56 12.21 1 60 0 0
#> 97 19.14 1 65 0 1
#> 51 18.23 1 83 0 1
#> 106.1 16.67 1 49 1 0
#> 159 10.55 1 50 0 1
#> 68 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 56.1 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 170 19.54 1 43 0 1
#> 55.1 19.34 1 69 0 1
#> 159.1 10.55 1 50 0 1
#> 189 10.51 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 158 20.14 1 74 1 0
#> 79 16.23 1 54 1 0
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 78 23.88 1 43 0 0
#> 159.2 10.55 1 50 0 1
#> 89.1 11.44 1 NA 0 0
#> 114.1 13.68 1 NA 0 0
#> 99 21.19 1 38 0 1
#> 78.1 23.88 1 43 0 0
#> 199.1 19.81 1 NA 0 1
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 133 14.65 1 57 0 0
#> 18 15.21 1 49 1 0
#> 57 14.46 1 45 0 1
#> 190 20.81 1 42 1 0
#> 189.1 10.51 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 177 12.53 1 75 0 0
#> 145 10.07 1 65 1 0
#> 145.1 10.07 1 65 1 0
#> 14 12.89 1 21 0 0
#> 129 23.41 1 53 1 0
#> 149.1 8.37 1 33 1 0
#> 190.1 20.81 1 42 1 0
#> 140 12.68 1 59 1 0
#> 128 20.35 1 35 0 1
#> 123 13.00 1 44 1 0
#> 184 17.77 1 38 0 0
#> 24.1 23.89 1 38 0 0
#> 90 20.94 1 50 0 1
#> 145.2 10.07 1 65 1 0
#> 77 7.27 1 67 0 1
#> 171 16.57 1 41 0 1
#> 57.1 14.46 1 45 0 1
#> 183 9.24 1 67 1 0
#> 81 14.06 1 34 0 0
#> 100.1 16.07 1 60 0 0
#> 101.1 9.97 1 10 0 1
#> 170.1 19.54 1 43 0 1
#> 66 22.13 1 53 0 0
#> 70 7.38 1 30 1 0
#> 91.1 5.33 1 61 0 1
#> 140.1 12.68 1 59 1 0
#> 91.2 5.33 1 61 0 1
#> 52 10.42 1 52 0 1
#> 6 15.64 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 68.1 20.62 1 44 0 0
#> 93.1 10.33 1 52 0 1
#> 92.1 22.92 1 47 0 1
#> 197 21.60 1 69 1 0
#> 25.1 6.32 1 34 1 0
#> 58 19.34 1 39 0 0
#> 85 16.44 1 36 0 0
#> 81.1 14.06 1 34 0 0
#> 166 19.98 1 48 0 0
#> 114.2 13.68 1 NA 0 0
#> 93.2 10.33 1 52 0 1
#> 175 21.91 1 43 0 0
#> 93.3 10.33 1 52 0 1
#> 16.1 8.71 1 71 0 1
#> 4 17.64 1 NA 0 1
#> 69.1 23.23 1 25 0 1
#> 93.4 10.33 1 52 0 1
#> 10 10.53 1 34 0 0
#> 149.2 8.37 1 33 1 0
#> 10.1 10.53 1 34 0 0
#> 169 22.41 1 46 0 0
#> 168 23.72 1 70 0 0
#> 189.2 10.51 1 NA 1 0
#> 190.2 20.81 1 42 1 0
#> 159.3 10.55 1 50 0 1
#> 108.1 18.29 1 39 0 1
#> 25.2 6.32 1 34 1 0
#> 4.1 17.64 1 NA 0 1
#> 61 10.12 1 36 0 1
#> 145.3 10.07 1 65 1 0
#> 93.5 10.33 1 52 0 1
#> 16.2 8.71 1 71 0 1
#> 58.1 19.34 1 39 0 0
#> 177.1 12.53 1 75 0 0
#> 171.1 16.57 1 41 0 1
#> 21 24.00 0 47 0 0
#> 165 24.00 0 47 0 0
#> 165.1 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 7 24.00 0 37 1 0
#> 118 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 62 24.00 0 71 0 0
#> 67 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 186 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 83.1 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 31 24.00 0 36 0 1
#> 118.1 24.00 0 44 1 0
#> 83.2 24.00 0 6 0 0
#> 156 24.00 0 50 1 0
#> 172 24.00 0 41 0 0
#> 144 24.00 0 28 0 1
#> 172.1 24.00 0 41 0 0
#> 185.1 24.00 0 44 1 0
#> 104 24.00 0 50 1 0
#> 83.3 24.00 0 6 0 0
#> 200 24.00 0 64 0 0
#> 7.1 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 144.1 24.00 0 28 0 1
#> 146 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 161 24.00 0 45 0 0
#> 163 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 143 24.00 0 51 0 0
#> 172.2 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 196 24.00 0 19 0 0
#> 160 24.00 0 31 1 0
#> 163.1 24.00 0 66 0 0
#> 172.3 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 48 24.00 0 31 1 0
#> 7.2 24.00 0 37 1 0
#> 193 24.00 0 45 0 1
#> 48.1 24.00 0 31 1 0
#> 7.3 24.00 0 37 1 0
#> 2 24.00 0 9 0 0
#> 75 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 19 24.00 0 57 0 1
#> 122.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 9 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 73 24.00 0 NA 0 1
#> 103 24.00 0 56 1 0
#> 46.1 24.00 0 71 0 0
#> 191.1 24.00 0 60 0 1
#> 176 24.00 0 43 0 1
#> 144.2 24.00 0 28 0 1
#> 74 24.00 0 43 0 1
#> 126.1 24.00 0 48 0 0
#> 7.4 24.00 0 37 1 0
#> 138 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 131 24.00 0 66 0 0
#> 73.1 24.00 0 NA 0 1
#> 54.1 24.00 0 53 1 0
#> 84 24.00 0 39 0 1
#> 115 24.00 0 NA 1 0
#> 64.1 24.00 0 43 0 0
#> 121 24.00 0 57 1 0
#> 186.1 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 73.2 24.00 0 NA 0 1
#> 62.1 24.00 0 71 0 0
#> 72 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 118.2 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.18 NA NA NA
#> 2 age, Cure model 0.0216 NA NA NA
#> 3 grade_ii, Cure model -0.0229 NA NA NA
#> 4 grade_iii, Cure model 1.23 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0104 NA NA NA
#> 2 grade_ii, Survival model 0.712 NA NA NA
#> 3 grade_iii, Survival model 0.726 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.1808 0.0216 -0.0229 1.2345
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 253.7
#> Residual Deviance: 235.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.18084089 0.02159535 -0.02290019 1.23446255
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01040954 0.71188538 0.72607319
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.9574833 0.4201240 0.7464230 0.6733036 0.9898242 0.9793357 0.7584720
#> [8] 0.3862832 0.7084622 0.1025616 0.8886231 0.8407915 0.6657097 0.6877258
#> [15] 0.7084622 0.8558849 0.5687692 0.7818873 0.8407915 0.6347868 0.6175422
#> [22] 0.6347868 0.8558849 0.7016177 0.5989190 0.7402877 0.9343270 0.8508905
#> [29] 0.2010924 0.8558849 0.5133841 0.2010924 0.5000317 0.9462055 0.7761188
#> [36] 0.7703152 0.7875756 0.5380110 0.3435815 0.8305862 0.9183240 0.9183240
#> [43] 0.8148474 0.3154585 0.9574833 0.5380110 0.8202304 0.5890358 0.8094558
#> [50] 0.6946886 0.1025616 0.5260543 0.9183240 0.9721848 0.7214856 0.7875756
#> [57] 0.9422747 0.7985475 0.7464230 0.9343270 0.6175422 0.4536870 0.9685176
#> [64] 0.9898242 0.8202304 0.9898242 0.8839872 0.7644051 0.9721848 0.5687692
#> [71] 0.8886231 0.3862832 0.4856782 0.9793357 0.6347868 0.7340186 0.7985475
#> [78] 0.6082768 0.8886231 0.4698363 0.8886231 0.9462055 0.3435815 0.8886231
#> [85] 0.8746146 0.9574833 0.8746146 0.4371033 0.2791241 0.5380110 0.8558849
#> [92] 0.6733036 0.9793357 0.9140725 0.9183240 0.8886231 0.9462055 0.6347868
#> [99] 0.8305862 0.7214856 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [106] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [113] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [120] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [127] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [134] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [141] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [148] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [155] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [162] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [169] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [176] 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000
#> [183] 0.0000000 0.0000000
#>
#> $Time
#> 149 113 100 108 91 25 26 92 106 24 93 56 97
#> 8.37 22.86 16.07 18.29 5.33 6.32 15.77 22.92 16.67 23.89 10.33 12.21 19.14
#> 51 106.1 159 68 96 56.1 55 170 55.1 159.1 30 158 79
#> 18.23 16.67 10.55 20.62 14.54 12.21 19.34 19.54 19.34 10.55 17.43 20.14 16.23
#> 101 49 78 159.2 99 78.1 153 16 133 18 57 190 69
#> 9.97 12.19 23.88 10.55 21.19 23.88 21.33 8.71 14.65 15.21 14.46 20.81 23.23
#> 177 145 145.1 14 129 149.1 190.1 140 128 123 184 24.1 90
#> 12.53 10.07 10.07 12.89 23.41 8.37 20.81 12.68 20.35 13.00 17.77 23.89 20.94
#> 145.2 77 171 57.1 183 81 100.1 101.1 170.1 66 70 91.1 140.1
#> 10.07 7.27 16.57 14.46 9.24 14.06 16.07 9.97 19.54 22.13 7.38 5.33 12.68
#> 91.2 52 6 77.1 68.1 93.1 92.1 197 25.1 58 85 81.1 166
#> 5.33 10.42 15.64 7.27 20.62 10.33 22.92 21.60 6.32 19.34 16.44 14.06 19.98
#> 93.2 175 93.3 16.1 69.1 93.4 10 149.2 10.1 169 168 190.2 159.3
#> 10.33 21.91 10.33 8.71 23.23 10.33 10.53 8.37 10.53 22.41 23.72 20.81 10.55
#> 108.1 25.2 61 145.3 93.5 16.2 58.1 177.1 171.1 21 165 165.1 3
#> 18.29 6.32 10.12 10.07 10.33 8.71 19.34 12.53 16.57 24.00 24.00 24.00 24.00
#> 83 7 118 122 12 191 126 62 67 173 141 185 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 46 34 1 83.1 28 31 118.1 83.2 156 172 144 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 104 83.3 200 7.1 102 144.1 146 102.1 161 163 64 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172.2 20 196 160 163.1 172.3 54 48 7.2 193 48.1 7.3 2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 17 19 122.1 120 9 87 103 46.1 191.1 176 144.2 74
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 126.1 7.4 138 75.1 131 54.1 84 64.1 121 186.1 65 62.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 118.2
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[63]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01252558 0.55184556 0.18871151
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.9364326 0.0177531 0.1084149
#> grade_iii, Cure model
#> 0.8444348
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 184 17.77 1 38 0 0
#> 10 10.53 1 34 0 0
#> 123 13.00 1 44 1 0
#> 51 18.23 1 83 0 1
#> 30 17.43 1 78 0 0
#> 18 15.21 1 49 1 0
#> 168 23.72 1 70 0 0
#> 36 21.19 1 48 0 1
#> 6 15.64 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 25 6.32 1 34 1 0
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 99 21.19 1 38 0 1
#> 85 16.44 1 36 0 0
#> 188 16.16 1 46 0 1
#> 130 16.47 1 53 0 1
#> 6.1 15.64 1 39 0 0
#> 158 20.14 1 74 1 0
#> 197 21.60 1 69 1 0
#> 189 10.51 1 NA 1 0
#> 181 16.46 1 45 0 1
#> 177 12.53 1 75 0 0
#> 51.1 18.23 1 83 0 1
#> 55.1 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 167 15.55 1 56 1 0
#> 79 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 194 22.40 1 38 0 1
#> 69 23.23 1 25 0 1
#> 18.1 15.21 1 49 1 0
#> 40 18.00 1 28 1 0
#> 81 14.06 1 34 0 0
#> 153 21.33 1 55 1 0
#> 197.1 21.60 1 69 1 0
#> 181.1 16.46 1 45 0 1
#> 192 16.44 1 31 1 0
#> 68 20.62 1 44 0 0
#> 140 12.68 1 59 1 0
#> 175 21.91 1 43 0 0
#> 52 10.42 1 52 0 1
#> 18.2 15.21 1 49 1 0
#> 70 7.38 1 30 1 0
#> 125 15.65 1 67 1 0
#> 101 9.97 1 10 0 1
#> 96 14.54 1 33 0 1
#> 78 23.88 1 43 0 0
#> 99.1 21.19 1 38 0 1
#> 153.1 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 18.3 15.21 1 49 1 0
#> 195 11.76 1 NA 1 0
#> 93 10.33 1 52 0 1
#> 25.1 6.32 1 34 1 0
#> 105.1 19.75 1 60 0 0
#> 187 9.92 1 39 1 0
#> 90 20.94 1 50 0 1
#> 189.1 10.51 1 NA 1 0
#> 41 18.02 1 40 1 0
#> 106 16.67 1 49 1 0
#> 85.1 16.44 1 36 0 0
#> 188.1 16.16 1 46 0 1
#> 177.1 12.53 1 75 0 0
#> 194.1 22.40 1 38 0 1
#> 41.1 18.02 1 40 1 0
#> 187.1 9.92 1 39 1 0
#> 57 14.46 1 45 0 1
#> 181.2 16.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 52.1 10.42 1 52 0 1
#> 177.2 12.53 1 75 0 0
#> 25.2 6.32 1 34 1 0
#> 189.2 10.51 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 129 23.41 1 53 1 0
#> 101.1 9.97 1 10 0 1
#> 50 10.02 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 50.1 10.02 1 NA 1 0
#> 169 22.41 1 46 0 0
#> 5 16.43 1 51 0 1
#> 157 15.10 1 47 0 0
#> 197.2 21.60 1 69 1 0
#> 175.1 21.91 1 43 0 0
#> 170 19.54 1 43 0 1
#> 81.1 14.06 1 34 0 0
#> 188.2 16.16 1 46 0 1
#> 50.2 10.02 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 177.3 12.53 1 75 0 0
#> 6.2 15.64 1 39 0 0
#> 155.1 13.08 1 26 0 0
#> 24 23.89 1 38 0 0
#> 194.2 22.40 1 38 0 1
#> 105.2 19.75 1 60 0 0
#> 180 14.82 1 37 0 0
#> 89 11.44 1 NA 0 0
#> 89.1 11.44 1 NA 0 0
#> 171 16.57 1 41 0 1
#> 97.1 19.14 1 65 0 1
#> 181.3 16.46 1 45 0 1
#> 134 17.81 1 47 1 0
#> 90.1 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 14 12.89 1 21 0 0
#> 164 23.60 1 76 0 1
#> 37 12.52 1 57 1 0
#> 171.1 16.57 1 41 0 1
#> 13 14.34 1 54 0 1
#> 178 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 118 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 176.1 24.00 0 43 0 1
#> 162 24.00 0 51 0 0
#> 54 24.00 0 53 1 0
#> 27 24.00 0 63 1 0
#> 21 24.00 0 47 0 0
#> 72 24.00 0 40 0 1
#> 80 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 12.1 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 1 24.00 0 23 1 0
#> 143.1 24.00 0 51 0 0
#> 19 24.00 0 57 0 1
#> 151 24.00 0 42 0 0
#> 115.1 24.00 0 NA 1 0
#> 87 24.00 0 27 0 0
#> 161 24.00 0 45 0 0
#> 160 24.00 0 31 1 0
#> 12.2 24.00 0 63 0 0
#> 54.1 24.00 0 53 1 0
#> 142 24.00 0 53 0 0
#> 173 24.00 0 19 0 1
#> 109 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 48 24.00 0 31 1 0
#> 151.1 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 1.1 24.00 0 23 1 0
#> 47 24.00 0 38 0 1
#> 173.1 24.00 0 19 0 1
#> 12.3 24.00 0 63 0 0
#> 131 24.00 0 66 0 0
#> 173.2 24.00 0 19 0 1
#> 3 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 34 24.00 0 36 0 0
#> 163 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 28 24.00 0 67 1 0
#> 72.1 24.00 0 40 0 1
#> 12.4 24.00 0 63 0 0
#> 151.2 24.00 0 42 0 0
#> 74 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 137.1 24.00 0 45 1 0
#> 65 24.00 0 57 1 0
#> 137.2 24.00 0 45 1 0
#> 48.1 24.00 0 31 1 0
#> 176.2 24.00 0 43 0 1
#> 152 24.00 0 36 0 1
#> 54.2 24.00 0 53 1 0
#> 7 24.00 0 37 1 0
#> 115.2 24.00 0 NA 1 0
#> 116 24.00 0 58 0 1
#> 144 24.00 0 28 0 1
#> 72.2 24.00 0 40 0 1
#> 138 24.00 0 44 1 0
#> 12.5 24.00 0 63 0 0
#> 144.1 24.00 0 28 0 1
#> 2 24.00 0 9 0 0
#> 144.2 24.00 0 28 0 1
#> 33 24.00 0 53 0 0
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 87.1 24.00 0 27 0 0
#> 80.1 24.00 0 41 0 0
#> 21.1 24.00 0 47 0 0
#> 7.1 24.00 0 37 1 0
#> 160.1 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 160.2 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 21.2 24.00 0 47 0 0
#> 148.1 24.00 0 61 1 0
#> 28.1 24.00 0 67 1 0
#> 17 24.00 0 38 0 1
#> 83 24.00 0 6 0 0
#> 152.1 24.00 0 36 0 1
#> 87.2 24.00 0 27 0 0
#> 141 24.00 0 44 1 0
#> 12.6 24.00 0 63 0 0
#> 160.3 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.936 NA NA NA
#> 2 age, Cure model 0.0178 NA NA NA
#> 3 grade_ii, Cure model 0.108 NA NA NA
#> 4 grade_iii, Cure model 0.844 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0125 NA NA NA
#> 2 grade_ii, Survival model 0.552 NA NA NA
#> 3 grade_iii, Survival model 0.189 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93643 0.01775 0.10841 0.84443
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 249.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.9364326 0.0177531 0.1084149 0.8444348
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01252558 0.55184556 0.18871151
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.2742999147 0.8271468018 0.6994838240 0.2168639363 0.2939963043
#> [6] 0.5434089495 0.0034725291 0.0847250890 0.4854438052 0.1724618096
#> [11] 0.9472389476 0.0188244993 0.5315821649 0.0847250890 0.3865890062
#> [16] 0.4407743285 0.3346528198 0.4854438052 0.1328851960 0.0544902808
#> [21] 0.3451116008 0.7498312375 0.2168639363 0.1724618096 0.7372695710
#> [26] 0.5198231740 0.4296768542 0.1896341241 0.0285998389 0.0145322526
#> [31] 0.5434089495 0.2550350617 0.6499918023 0.0721388495 0.0544902808
#> [36] 0.3451116008 0.3865890062 0.1180100720 0.7246321931 0.0430627545
#> [41] 0.8403996736 0.5434089495 0.9338515008 0.4740229034 0.8804882240
#> [46] 0.6134482010 0.0015142215 0.0847250890 0.0721388495 0.8139671662
#> [51] 0.1405058894 0.5434089495 0.8670047950 0.9472389476 0.1405058894
#> [56] 0.9071954922 0.1040535790 0.2359892922 0.3041374256 0.3865890062
#> [61] 0.4407743285 0.7498312375 0.0285998389 0.2359892922 0.9071954922
#> [66] 0.6255501694 0.3451116008 0.9866156216 0.8403996736 0.7498312375
#> [71] 0.9472389476 0.2075619315 0.0103908957 0.8804882240 0.6746116266
#> [76] 0.0234888889 0.4186128539 0.5894289165 0.0544902808 0.0430627545
#> [81] 0.1640722092 0.6499918023 0.4407743285 0.1253988511 0.7498312375
#> [86] 0.4854438052 0.6746116266 0.0003028019 0.0285998389 0.1405058894
#> [91] 0.6013940821 0.3142989161 0.1896341241 0.3451116008 0.2646611266
#> [96] 0.1040535790 0.2840687286 0.7120323273 0.0064353147 0.8008610138
#> [101] 0.3142989161 0.6377257923 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000
#>
#> $Time
#> 184 10 123 51 30 18 168 36 6 55 25 113 29
#> 17.77 10.53 13.00 18.23 17.43 15.21 23.72 21.19 15.64 19.34 6.32 22.86 15.45
#> 99 85 188 130 6.1 158 197 181 177 51.1 55.1 154 167
#> 21.19 16.44 16.16 16.47 15.64 20.14 21.60 16.46 12.53 18.23 19.34 12.63 15.55
#> 79 97 194 69 18.1 40 81 153 197.1 181.1 192 68 140
#> 16.23 19.14 22.40 23.23 15.21 18.00 14.06 21.33 21.60 16.46 16.44 20.62 12.68
#> 175 52 18.2 70 125 101 96 78 99.1 153.1 42 105 18.3
#> 21.91 10.42 15.21 7.38 15.65 9.97 14.54 23.88 21.19 21.33 12.43 19.75 15.21
#> 93 25.1 105.1 187 90 41 106 85.1 188.1 177.1 194.1 41.1 187.1
#> 10.33 6.32 19.75 9.92 20.94 18.02 16.67 16.44 16.16 12.53 22.40 18.02 9.92
#> 57 181.2 127 52.1 177.2 25.2 8 129 101.1 155 169 5 157
#> 14.46 16.46 3.53 10.42 12.53 6.32 18.43 23.41 9.97 13.08 22.41 16.43 15.10
#> 197.2 175.1 170 81.1 188.2 128 177.3 6.2 155.1 24 194.2 105.2 180
#> 21.60 21.91 19.54 14.06 16.16 20.35 12.53 15.64 13.08 23.89 22.40 19.75 14.82
#> 171 97.1 181.3 134 90.1 110 14 164 37 171.1 13 178 12
#> 16.57 19.14 16.46 17.81 20.94 17.56 12.89 23.60 12.52 16.57 14.34 24.00 24.00
#> 176 118 137 176.1 162 54 27 21 72 80 20 12.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 143.1 19 151 87 161 160 12.2 54.1 142 173 109 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48 151.1 102 1.1 47 173.1 12.3 131 173.2 3 20.1 34 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 28 72.1 12.4 151.2 74 148 137.1 65 137.2 48.1 176.2 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54.2 7 116 144 72.2 138 12.5 144.1 2 144.2 33 122 104
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 87.1 80.1 21.1 7.1 160.1 174 160.2 112 21.2 148.1 28.1 17 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 87.2 141 12.6 160.3
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[64]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.0003906222 0.6083245513 0.2961966279
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.44994301 0.00813705 0.18996803
#> grade_iii, Cure model
#> 0.66512028
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 41 18.02 1 40 1 0
#> 149 8.37 1 33 1 0
#> 41.1 18.02 1 40 1 0
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 69 23.23 1 25 0 1
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 134 17.81 1 47 1 0
#> 29 15.45 1 68 1 0
#> 199 19.81 1 NA 0 1
#> 50 10.02 1 NA 1 0
#> 96 14.54 1 33 0 1
#> 36 21.19 1 48 0 1
#> 92 22.92 1 47 0 1
#> 110 17.56 1 65 0 1
#> 100 16.07 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 56 12.21 1 60 0 0
#> 30 17.43 1 78 0 0
#> 86 23.81 1 58 0 1
#> 42 12.43 1 49 0 1
#> 110.1 17.56 1 65 0 1
#> 92.1 22.92 1 47 0 1
#> 58 19.34 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 85 16.44 1 36 0 0
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 166 19.98 1 48 0 0
#> 180 14.82 1 37 0 0
#> 42.1 12.43 1 49 0 1
#> 188 16.16 1 46 0 1
#> 158 20.14 1 74 1 0
#> 78 23.88 1 43 0 0
#> 26 15.77 1 49 0 1
#> 76 19.22 1 54 0 1
#> 52 10.42 1 52 0 1
#> 50.1 10.02 1 NA 1 0
#> 59 10.16 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 184 17.77 1 38 0 0
#> 41.2 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 96.1 14.54 1 33 0 1
#> 81 14.06 1 34 0 0
#> 197 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 88.1 18.37 1 47 0 0
#> 15 22.68 1 48 0 0
#> 134.1 17.81 1 47 1 0
#> 133 14.65 1 57 0 0
#> 184.1 17.77 1 38 0 0
#> 108.1 18.29 1 39 0 1
#> 6 15.64 1 39 0 0
#> 195.1 11.76 1 NA 1 0
#> 114 13.68 1 NA 0 0
#> 68 20.62 1 44 0 0
#> 150 20.33 1 48 0 0
#> 134.2 17.81 1 47 1 0
#> 175 21.91 1 43 0 0
#> 42.2 12.43 1 49 0 1
#> 81.1 14.06 1 34 0 0
#> 188.1 16.16 1 46 0 1
#> 42.3 12.43 1 49 0 1
#> 66 22.13 1 53 0 0
#> 159 10.55 1 50 0 1
#> 167 15.55 1 56 1 0
#> 106 16.67 1 49 1 0
#> 155 13.08 1 26 0 0
#> 167.1 15.55 1 56 1 0
#> 140 12.68 1 59 1 0
#> 123 13.00 1 44 1 0
#> 85.1 16.44 1 36 0 0
#> 166.1 19.98 1 48 0 0
#> 108.2 18.29 1 39 0 1
#> 190 20.81 1 42 1 0
#> 145 10.07 1 65 1 0
#> 69.1 23.23 1 25 0 1
#> 96.2 14.54 1 33 0 1
#> 10 10.53 1 34 0 0
#> 43 12.10 1 61 0 1
#> 136.1 21.83 1 43 0 1
#> 171 16.57 1 41 0 1
#> 159.1 10.55 1 50 0 1
#> 195.2 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 14 12.89 1 21 0 0
#> 50.2 10.02 1 NA 1 0
#> 158.1 20.14 1 74 1 0
#> 78.1 23.88 1 43 0 0
#> 150.1 20.33 1 48 0 0
#> 13 14.34 1 54 0 1
#> 68.1 20.62 1 44 0 0
#> 86.1 23.81 1 58 0 1
#> 32 20.90 1 37 1 0
#> 114.1 13.68 1 NA 0 0
#> 14.1 12.89 1 21 0 0
#> 30.1 17.43 1 78 0 0
#> 55 19.34 1 69 0 1
#> 168 23.72 1 70 0 0
#> 108.3 18.29 1 39 0 1
#> 24 23.89 1 38 0 0
#> 15.1 22.68 1 48 0 0
#> 15.2 22.68 1 48 0 0
#> 41.3 18.02 1 40 1 0
#> 45 17.42 1 54 0 1
#> 105.1 19.75 1 60 0 0
#> 181 16.46 1 45 0 1
#> 63 22.77 1 31 1 0
#> 90 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 112 24.00 0 61 0 0
#> 82 24.00 0 34 0 0
#> 143 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 82.1 24.00 0 34 0 0
#> 160 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 186 24.00 0 45 1 0
#> 173 24.00 0 19 0 1
#> 95 24.00 0 68 0 1
#> 31 24.00 0 36 0 1
#> 94 24.00 0 51 0 1
#> 94.1 24.00 0 51 0 1
#> 95.1 24.00 0 68 0 1
#> 31.1 24.00 0 36 0 1
#> 196 24.00 0 19 0 0
#> 148 24.00 0 61 1 0
#> 119 24.00 0 17 0 0
#> 182.1 24.00 0 35 0 0
#> 82.2 24.00 0 34 0 0
#> 65 24.00 0 57 1 0
#> 174 24.00 0 49 1 0
#> 126 24.00 0 48 0 0
#> 152 24.00 0 36 0 1
#> 121 24.00 0 57 1 0
#> 21 24.00 0 47 0 0
#> 126.1 24.00 0 48 0 0
#> 163 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 62.1 24.00 0 71 0 0
#> 1 24.00 0 23 1 0
#> 160.1 24.00 0 31 1 0
#> 173.1 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 17 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 94.2 24.00 0 51 0 1
#> 174.1 24.00 0 49 1 0
#> 34 24.00 0 36 0 0
#> 135 24.00 0 58 1 0
#> 132 24.00 0 55 0 0
#> 34.1 24.00 0 36 0 0
#> 94.3 24.00 0 51 0 1
#> 1.1 24.00 0 23 1 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 20 24.00 0 46 1 0
#> 71 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 122 24.00 0 66 0 0
#> 46.1 24.00 0 71 0 0
#> 82.3 24.00 0 34 0 0
#> 21.1 24.00 0 47 0 0
#> 31.2 24.00 0 36 0 1
#> 67 24.00 0 25 0 0
#> 17.1 24.00 0 38 0 1
#> 116 24.00 0 58 0 1
#> 131 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 163.1 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 163.2 24.00 0 66 0 0
#> 27 24.00 0 63 1 0
#> 65.1 24.00 0 57 1 0
#> 98 24.00 0 34 1 0
#> 94.4 24.00 0 51 0 1
#> 193 24.00 0 45 0 1
#> 115.1 24.00 0 NA 1 0
#> 83 24.00 0 6 0 0
#> 34.2 24.00 0 36 0 0
#> 121.1 24.00 0 57 1 0
#> 176 24.00 0 43 0 1
#> 73.1 24.00 0 NA 0 1
#> 182.2 24.00 0 35 0 0
#> 82.4 24.00 0 34 0 0
#> 67.1 24.00 0 25 0 0
#> 156 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 174.2 24.00 0 49 1 0
#> 11 24.00 0 42 0 1
#> 142 24.00 0 53 0 0
#> 131.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 142.1 24.00 0 53 0 0
#> 185 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.450 NA NA NA
#> 2 age, Cure model 0.00814 NA NA NA
#> 3 grade_ii, Cure model 0.190 NA NA NA
#> 4 grade_iii, Cure model 0.665 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.000391 NA NA NA
#> 2 grade_ii, Survival model 0.608 NA NA NA
#> 3 grade_iii, Survival model 0.296 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.449943 0.008137 0.189968 0.665120
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 250.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.44994301 0.00813705 0.18996803 0.66512028
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.0003906222 0.6083245513 0.2961966279
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.53376740 0.99275747 0.53376740 0.49603511 0.97074959 0.12123633
#> [7] 0.47623549 0.22481356 0.56932411 0.75500302 0.77914812 0.29847985
#> [13] 0.14950178 0.61247591 0.71393574 0.90354232 0.62962424 0.07417645
#> [19] 0.87341498 0.61247591 0.14950178 0.44625424 0.68067616 0.91116868
#> [25] 0.91116868 0.40593720 0.76305284 0.87341498 0.69737912 0.38574868
#> [31] 0.03849228 0.72226031 0.46622285 0.95591883 0.42610694 0.59514355
#> [37] 0.53376740 0.26283147 0.77914812 0.81070309 0.28671999 0.96334484
#> [43] 0.47623549 0.18882979 0.56932411 0.77110143 0.59514355 0.49603511
#> [49] 0.73054946 0.34337429 0.36457296 0.56932411 0.25017065 0.87341498
#> [55] 0.81070309 0.69737912 0.87341498 0.23749910 0.93363311 0.73883717
#> [61] 0.65533991 0.82647286 0.73883717 0.85789100 0.83439495 0.68067616
#> [67] 0.40593720 0.49603511 0.33259460 0.97813386 0.12123633 0.77914812
#> [73] 0.94847128 0.92613992 0.26283147 0.66382467 0.93363311 0.98546914
#> [79] 0.84225220 0.38574868 0.03849228 0.36457296 0.80277742 0.34337429
#> [85] 0.07417645 0.32150303 0.84225220 0.62962424 0.44625424 0.10471879
#> [91] 0.49603511 0.01437070 0.18882979 0.18882979 0.53376740 0.64675817
#> [97] 0.42610694 0.67226987 0.17593901 0.31007074 0.86568357 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 41 149 41.1 108 61 69 88 169 134 29 96 36 92
#> 18.02 8.37 18.02 18.29 10.12 23.23 18.37 22.41 17.81 15.45 14.54 21.19 22.92
#> 110 100 56 30 86 42 110.1 92.1 58 85 49 49.1 166
#> 17.56 16.07 12.21 17.43 23.81 12.43 17.56 22.92 19.34 16.44 12.19 12.19 19.98
#> 180 42.1 188 158 78 26 76 52 105 184 41.2 136 96.1
#> 14.82 12.43 16.16 20.14 23.88 15.77 19.22 10.42 19.75 17.77 18.02 21.83 14.54
#> 81 197 93 88.1 15 134.1 133 184.1 108.1 6 68 150 134.2
#> 14.06 21.60 10.33 18.37 22.68 17.81 14.65 17.77 18.29 15.64 20.62 20.33 17.81
#> 175 42.2 81.1 188.1 42.3 66 159 167 106 155 167.1 140 123
#> 21.91 12.43 14.06 16.16 12.43 22.13 10.55 15.55 16.67 13.08 15.55 12.68 13.00
#> 85.1 166.1 108.2 190 145 69.1 96.2 10 43 136.1 171 159.1 187
#> 16.44 19.98 18.29 20.81 10.07 23.23 14.54 10.53 12.10 21.83 16.57 10.55 9.92
#> 14 158.1 78.1 150.1 13 68.1 86.1 32 14.1 30.1 55 168 108.3
#> 12.89 20.14 23.88 20.33 14.34 20.62 23.81 20.90 12.89 17.43 19.34 23.72 18.29
#> 24 15.1 15.2 41.3 45 105.1 181 63 90 37 112 82 143
#> 23.89 22.68 22.68 18.02 17.42 19.75 16.46 22.77 20.94 12.52 24.00 24.00 24.00
#> 82.1 160 62 182 186 173 95 31 94 94.1 95.1 31.1 196
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 119 182.1 82.2 65 174 126 152 121 21 126.1 163 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.1 1 160.1 173.1 172 17 33 94.2 174.1 34 135 132 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.3 1.1 9 75 20 71 165 122 46.1 82.3 21.1 31.2 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.1 116 131 87 163.1 103 163.2 27 65.1 98 94.4 193 83
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.2 121.1 176 182.2 82.4 67.1 156 191 174.2 11 142 131.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 185 35
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[65]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.007852926 1.199847554 0.514071907
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.74010840 0.01554105 -0.27655265
#> grade_iii, Cure model
#> 0.72778984
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 52 10.42 1 52 0 1
#> 29 15.45 1 68 1 0
#> 36 21.19 1 48 0 1
#> 51 18.23 1 83 0 1
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 177 12.53 1 75 0 0
#> 49 12.19 1 48 1 0
#> 134 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 175 21.91 1 43 0 0
#> 24 23.89 1 38 0 0
#> 41 18.02 1 40 1 0
#> 50 10.02 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 110 17.56 1 65 0 1
#> 90 20.94 1 50 0 1
#> 194 22.40 1 38 0 1
#> 124 9.73 1 NA 1 0
#> 6 15.64 1 39 0 0
#> 183 9.24 1 67 1 0
#> 23 16.92 1 61 0 0
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 61 10.12 1 36 0 1
#> 4.1 17.64 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 52.1 10.42 1 52 0 1
#> 25 6.32 1 34 1 0
#> 51.1 18.23 1 83 0 1
#> 69 23.23 1 25 0 1
#> 56 12.21 1 60 0 0
#> 10 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 180 14.82 1 37 0 0
#> 194.1 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 169 22.41 1 46 0 0
#> 155 13.08 1 26 0 0
#> 52.2 10.42 1 52 0 1
#> 86 23.81 1 58 0 1
#> 36.1 21.19 1 48 0 1
#> 92 22.92 1 47 0 1
#> 167 15.55 1 56 1 0
#> 39 15.59 1 37 0 1
#> 199.1 19.81 1 NA 0 1
#> 175.1 21.91 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 86.1 23.81 1 58 0 1
#> 155.1 13.08 1 26 0 0
#> 97 19.14 1 65 0 1
#> 106 16.67 1 49 1 0
#> 52.3 10.42 1 52 0 1
#> 180.1 14.82 1 37 0 0
#> 45 17.42 1 54 0 1
#> 70 7.38 1 30 1 0
#> 16 8.71 1 71 0 1
#> 24.1 23.89 1 38 0 0
#> 153 21.33 1 55 1 0
#> 169.1 22.41 1 46 0 0
#> 183.1 9.24 1 67 1 0
#> 49.1 12.19 1 48 1 0
#> 130 16.47 1 53 0 1
#> 91 5.33 1 61 0 1
#> 68 20.62 1 44 0 0
#> 91.1 5.33 1 61 0 1
#> 52.4 10.42 1 52 0 1
#> 13 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 36.2 21.19 1 48 0 1
#> 52.5 10.42 1 52 0 1
#> 184 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 154 12.63 1 20 1 0
#> 169.2 22.41 1 46 0 0
#> 194.2 22.40 1 38 0 1
#> 97.1 19.14 1 65 0 1
#> 26 15.77 1 49 0 1
#> 51.2 18.23 1 83 0 1
#> 91.2 5.33 1 61 0 1
#> 113 22.86 1 34 0 0
#> 96 14.54 1 33 0 1
#> 77 7.27 1 67 0 1
#> 36.3 21.19 1 48 0 1
#> 58 19.34 1 39 0 0
#> 18 15.21 1 49 1 0
#> 37 12.52 1 57 1 0
#> 24.2 23.89 1 38 0 0
#> 114.1 13.68 1 NA 0 0
#> 61.1 10.12 1 36 0 1
#> 150 20.33 1 48 0 0
#> 124.1 9.73 1 NA 1 0
#> 140 12.68 1 59 1 0
#> 14 12.89 1 21 0 0
#> 107 11.18 1 54 1 0
#> 194.3 22.40 1 38 0 1
#> 77.1 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 128 20.35 1 35 0 1
#> 29.1 15.45 1 68 1 0
#> 153.1 21.33 1 55 1 0
#> 59 10.16 1 NA 1 0
#> 70.1 7.38 1 30 1 0
#> 96.1 14.54 1 33 0 1
#> 42 12.43 1 49 0 1
#> 25.1 6.32 1 34 1 0
#> 10.1 10.53 1 34 0 0
#> 169.3 22.41 1 46 0 0
#> 187 9.92 1 39 1 0
#> 23.1 16.92 1 61 0 0
#> 11 24.00 0 42 0 1
#> 11.1 24.00 0 42 0 1
#> 131 24.00 0 66 0 0
#> 119 24.00 0 17 0 0
#> 7 24.00 0 37 1 0
#> 74 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 47 24.00 0 38 0 1
#> 176 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 142 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 7.1 24.00 0 37 1 0
#> 143 24.00 0 51 0 0
#> 119.1 24.00 0 17 0 0
#> 198.1 24.00 0 66 0 1
#> 141 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 44 24.00 0 56 0 0
#> 65 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 9 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 141.1 24.00 0 44 1 0
#> 119.2 24.00 0 17 0 0
#> 118 24.00 0 44 1 0
#> 118.1 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 54 24.00 0 53 1 0
#> 161 24.00 0 45 0 0
#> 102 24.00 0 49 0 0
#> 80 24.00 0 41 0 0
#> 1 24.00 0 23 1 0
#> 21 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 62 24.00 0 71 0 0
#> 103 24.00 0 56 1 0
#> 142.1 24.00 0 53 0 0
#> 11.2 24.00 0 42 0 1
#> 173.1 24.00 0 19 0 1
#> 137 24.00 0 45 1 0
#> 7.2 24.00 0 37 1 0
#> 20.1 24.00 0 46 1 0
#> 112 24.00 0 61 0 0
#> 20.2 24.00 0 46 1 0
#> 119.3 24.00 0 17 0 0
#> 156 24.00 0 50 1 0
#> 74.1 24.00 0 43 0 1
#> 160 24.00 0 31 1 0
#> 62.1 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 104 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 20.3 24.00 0 46 1 0
#> 122 24.00 0 66 0 0
#> 54.1 24.00 0 53 1 0
#> 165 24.00 0 47 0 0
#> 17 24.00 0 38 0 1
#> 104.1 24.00 0 50 1 0
#> 47.1 24.00 0 38 0 1
#> 64 24.00 0 43 0 0
#> 17.1 24.00 0 38 0 1
#> 71 24.00 0 51 0 0
#> 53 24.00 0 32 0 1
#> 53.1 24.00 0 32 0 1
#> 33 24.00 0 53 0 0
#> 172 24.00 0 41 0 0
#> 75.1 24.00 0 21 1 0
#> 95 24.00 0 68 0 1
#> 132 24.00 0 55 0 0
#> 131.1 24.00 0 66 0 0
#> 193 24.00 0 45 0 1
#> 109.1 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 178 24.00 0 52 1 0
#> 131.2 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 12 24.00 0 63 0 0
#> 73 24.00 0 NA 0 1
#> 178.1 24.00 0 52 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.740 NA NA NA
#> 2 age, Cure model 0.0155 NA NA NA
#> 3 grade_ii, Cure model -0.277 NA NA NA
#> 4 grade_iii, Cure model 0.728 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00785 NA NA NA
#> 2 grade_ii, Survival model 1.20 NA NA NA
#> 3 grade_iii, Survival model 0.514 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74011 0.01554 -0.27655 0.72779
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 249.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.74010840 0.01554105 -0.27655265 0.72778984
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.007852926 1.199847554 0.514071907
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91585399 0.78177093 0.53167239 0.66170387 0.60846737 0.64446348
#> [7] 0.86403605 0.88382310 0.69303021 0.48275700 0.08755443 0.68536643
#> [13] 0.18387511 0.70771265 0.57037266 0.41474268 0.76252152 0.95409270
#> [19] 0.72199141 0.74932970 0.46882558 0.94140040 0.64446348 0.81023126
#> [25] 0.91585399 0.98156572 0.66170387 0.29043873 0.87893897 0.90687499
#> [31] 0.79901468 0.41474268 0.84314803 0.35013140 0.83229506 0.91585399
#> [37] 0.24625707 0.53167239 0.31169967 0.77552136 0.76905538 0.48275700
#> [43] 0.18387511 0.24625707 0.83229506 0.62701474 0.73592263 0.91585399
#> [49] 0.79901468 0.71490746 0.96613220 0.96213484 0.08755443 0.50960493
#> [55] 0.35013140 0.95409270 0.88382310 0.74267261 0.98903217 0.58005526
#> [61] 0.98903217 0.91585399 0.82683458 0.53167239 0.91585399 0.70038481
#> [67] 0.90236061 0.85895061 0.35013140 0.41474268 0.62701474 0.75596753
#> [73] 0.66170387 0.98903217 0.33108597 0.81583712 0.97390490 0.53167239
#> [79] 0.61776600 0.79335971 0.86909760 0.08755443 0.94140040 0.59910323
#> [85] 0.85377683 0.84846541 0.89781264 0.41474268 0.97390490 0.89316887
#> [91] 0.58967161 0.78177093 0.50960493 0.96613220 0.81583712 0.87403846
#> [97] 0.98156572 0.90687499 0.35013140 0.94989955 0.72199141 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 52 29 36 51 166 88 177 49 134 175 24 41 78
#> 10.42 15.45 21.19 18.23 19.98 18.37 12.53 12.19 17.81 21.91 23.89 18.02 23.88
#> 110 90 194 6 183 23 85 66 61 88.1 133 52.1 25
#> 17.56 20.94 22.40 15.64 9.24 16.92 16.44 22.13 10.12 18.37 14.65 10.42 6.32
#> 51.1 69 56 10 180 194.1 123 169 155 52.2 86 36.1 92
#> 18.23 23.23 12.21 10.53 14.82 22.40 13.00 22.41 13.08 10.42 23.81 21.19 22.92
#> 167 39 175.1 78.1 86.1 155.1 97 106 52.3 180.1 45 70 16
#> 15.55 15.59 21.91 23.88 23.81 13.08 19.14 16.67 10.42 14.82 17.42 7.38 8.71
#> 24.1 153 169.1 183.1 49.1 130 91 68 91.1 52.4 13 36.2 52.5
#> 23.89 21.33 22.41 9.24 12.19 16.47 5.33 20.62 5.33 10.42 14.34 21.19 10.42
#> 184 159 154 169.2 194.2 97.1 26 51.2 91.2 113 96 77 36.3
#> 17.77 10.55 12.63 22.41 22.40 19.14 15.77 18.23 5.33 22.86 14.54 7.27 21.19
#> 58 18 37 24.2 61.1 150 140 14 107 194.3 77.1 43 128
#> 19.34 15.21 12.52 23.89 10.12 20.33 12.68 12.89 11.18 22.40 7.27 12.10 20.35
#> 29.1 153.1 70.1 96.1 42 25.1 10.1 169.3 187 23.1 11 11.1 131
#> 15.45 21.33 7.38 14.54 12.43 6.32 10.53 22.41 9.92 16.92 24.00 24.00 24.00
#> 119 7 74 198 47 176 31 173 142 186 75 7.1 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 198.1 141 196 44 65 116 9 163 141.1 119.2 118 118.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 54 161 102 80 1 21 3 20 151 146 62 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 11.2 173.1 137 7.2 20.1 112 20.2 119.3 156 74.1 160 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109 35 104 83 20.3 122 54.1 165 17 104.1 47.1 64 17.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 53 53.1 33 172 75.1 95 132 131.1 193 109.1 163.1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 178 131.2 22 12 178.1
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[66]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01259953 0.89524408 0.26291908
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.42602142 -0.01033608 0.15731393
#> grade_iii, Cure model
#> 0.64764357
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 129 23.41 1 53 1 0
#> 194 22.40 1 38 0 1
#> 140 12.68 1 59 1 0
#> 18 15.21 1 49 1 0
#> 134 17.81 1 47 1 0
#> 8 18.43 1 32 0 0
#> 78 23.88 1 43 0 0
#> 13 14.34 1 54 0 1
#> 13.1 14.34 1 54 0 1
#> 108 18.29 1 39 0 1
#> 52 10.42 1 52 0 1
#> 170 19.54 1 43 0 1
#> 164 23.60 1 76 0 1
#> 68 20.62 1 44 0 0
#> 154 12.63 1 20 1 0
#> 188 16.16 1 46 0 1
#> 123 13.00 1 44 1 0
#> 179 18.63 1 42 0 0
#> 25 6.32 1 34 1 0
#> 16 8.71 1 71 0 1
#> 10 10.53 1 34 0 0
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 41 18.02 1 40 1 0
#> 136 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 92 22.92 1 47 0 1
#> 184 17.77 1 38 0 0
#> 40 18.00 1 28 1 0
#> 39 15.59 1 37 0 1
#> 192 16.44 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 93 10.33 1 52 0 1
#> 183 9.24 1 67 1 0
#> 81 14.06 1 34 0 0
#> 86 23.81 1 58 0 1
#> 192.2 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 190 20.81 1 42 1 0
#> 113 22.86 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 81.1 14.06 1 34 0 0
#> 127 3.53 1 62 0 1
#> 100 16.07 1 60 0 0
#> 179.1 18.63 1 42 0 0
#> 183.1 9.24 1 67 1 0
#> 101 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 8.1 18.43 1 32 0 0
#> 92.1 22.92 1 47 0 1
#> 125 15.65 1 67 1 0
#> 175 21.91 1 43 0 0
#> 45 17.42 1 54 0 1
#> 117 17.46 1 26 0 1
#> 183.2 9.24 1 67 1 0
#> 41.1 18.02 1 40 1 0
#> 155 13.08 1 26 0 0
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 170.1 19.54 1 43 0 1
#> 16.1 8.71 1 71 0 1
#> 78.1 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 100.1 16.07 1 60 0 0
#> 88 18.37 1 47 0 0
#> 197 21.60 1 69 1 0
#> 61 10.12 1 36 0 1
#> 92.2 22.92 1 47 0 1
#> 179.2 18.63 1 42 0 0
#> 49.1 12.19 1 48 1 0
#> 29 15.45 1 68 1 0
#> 29.1 15.45 1 68 1 0
#> 192.3 16.44 1 31 1 0
#> 159 10.55 1 50 0 1
#> 197.1 21.60 1 69 1 0
#> 36 21.19 1 48 0 1
#> 18.1 15.21 1 49 1 0
#> 114 13.68 1 NA 0 0
#> 86.1 23.81 1 58 0 1
#> 6 15.64 1 39 0 0
#> 23 16.92 1 61 0 0
#> 25.1 6.32 1 34 1 0
#> 164.1 23.60 1 76 0 1
#> 81.2 14.06 1 34 0 0
#> 61.1 10.12 1 36 0 1
#> 105 19.75 1 60 0 0
#> 76 19.22 1 54 0 1
#> 167 15.55 1 56 1 0
#> 179.3 18.63 1 42 0 0
#> 194.1 22.40 1 38 0 1
#> 105.1 19.75 1 60 0 0
#> 168 23.72 1 70 0 0
#> 57 14.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 192.4 16.44 1 31 1 0
#> 167.1 15.55 1 56 1 0
#> 124 9.73 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 79 16.23 1 54 1 0
#> 166 19.98 1 48 0 0
#> 5 16.43 1 51 0 1
#> 77 7.27 1 67 0 1
#> 149 8.37 1 33 1 0
#> 88.1 18.37 1 47 0 0
#> 181 16.46 1 45 0 1
#> 124.1 9.73 1 NA 1 0
#> 166.1 19.98 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 40.1 18.00 1 28 1 0
#> 154.1 12.63 1 20 1 0
#> 29.2 15.45 1 68 1 0
#> 66 22.13 1 53 0 0
#> 67 24.00 0 25 0 0
#> 98 24.00 0 34 1 0
#> 82 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 186 24.00 0 45 1 0
#> 62 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 143 24.00 0 51 0 0
#> 112 24.00 0 61 0 0
#> 186.1 24.00 0 45 1 0
#> 141 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 31 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 121 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 102 24.00 0 49 0 0
#> 1 24.00 0 23 1 0
#> 95 24.00 0 68 0 1
#> 74 24.00 0 43 0 1
#> 74.1 24.00 0 43 0 1
#> 142 24.00 0 53 0 0
#> 109.1 24.00 0 48 0 0
#> 121.1 24.00 0 57 1 0
#> 109.2 24.00 0 48 0 0
#> 191 24.00 0 60 0 1
#> 178 24.00 0 52 1 0
#> 21 24.00 0 47 0 0
#> 143.2 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 138 24.00 0 44 1 0
#> 147 24.00 0 76 1 0
#> 156.1 24.00 0 50 1 0
#> 160 24.00 0 31 1 0
#> 178.1 24.00 0 52 1 0
#> 19.1 24.00 0 57 0 1
#> 34 24.00 0 36 0 0
#> 143.3 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 17 24.00 0 38 0 1
#> 28 24.00 0 67 1 0
#> 118 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 112.1 24.00 0 61 0 0
#> 46 24.00 0 71 0 0
#> 46.1 24.00 0 71 0 0
#> 28.1 24.00 0 67 1 0
#> 147.1 24.00 0 76 1 0
#> 94 24.00 0 51 0 1
#> 102.1 24.00 0 49 0 0
#> 122 24.00 0 66 0 0
#> 173 24.00 0 19 0 1
#> 115 24.00 0 NA 1 0
#> 121.2 24.00 0 57 1 0
#> 67.1 24.00 0 25 0 0
#> 11 24.00 0 42 0 1
#> 148.1 24.00 0 61 1 0
#> 185.1 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 2 24.00 0 9 0 0
#> 19.2 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 12.1 24.00 0 63 0 0
#> 109.3 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 176.1 24.00 0 43 0 1
#> 200.1 24.00 0 64 0 0
#> 165 24.00 0 47 0 0
#> 138.1 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 47 24.00 0 38 0 1
#> 104 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 120 24.00 0 68 0 1
#> 74.2 24.00 0 43 0 1
#> 104.1 24.00 0 50 1 0
#> 143.4 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.426 NA NA NA
#> 2 age, Cure model -0.0103 NA NA NA
#> 3 grade_ii, Cure model 0.157 NA NA NA
#> 4 grade_iii, Cure model 0.648 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0126 NA NA NA
#> 2 grade_ii, Survival model 0.895 NA NA NA
#> 3 grade_iii, Survival model 0.263 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.42602 -0.01034 0.15731 0.64764
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 263.3
#> Residual Deviance: 259.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.42602142 -0.01033608 0.15731393 0.64764357
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01259953 0.89524408 0.26291908
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.0294846660 0.0616500510 0.7370871220 0.6203023544 0.3584743830
#> [6] 0.2480147298 0.0009620377 0.6621264590 0.6621264590 0.2918581086
#> [11] 0.8208228038 0.1788343708 0.0174874617 0.1340637977 0.7478885984
#> [16] 0.5048601702 0.7262596255 0.2079392552 0.9685587775 0.9261237141
#> [21] 0.8103401279 0.3906929526 0.6410428490 0.3150456326 0.0923909767
#> [26] 0.7687944707 0.0358938405 0.3691286379 0.3372627837 0.5574122414
#> [31] 0.4348967301 0.4348967301 0.8418272654 0.8948326758 0.6833151839
#> [36] 0.0053674992 0.4348967301 0.3033315847 0.1257198087 0.0543146792
#> [41] 0.8208228038 0.6833151839 0.9894522459 0.5152234112 0.2079392552
#> [46] 0.8948326758 0.8736215629 0.8842587652 0.2480147298 0.0358938405
#> [51] 0.5361842817 0.0840734951 0.4015689955 0.3799012040 0.8948326758
#> [56] 0.3150456326 0.7153661699 0.1788343708 0.9261237141 0.0009620377
#> [61] 0.7895105170 0.5152234112 0.2695379079 0.1008951686 0.8524390650
#> [66] 0.0358938405 0.2079392552 0.7687944707 0.5891221739 0.5891221739
#> [71] 0.4348967301 0.7999044915 0.1008951686 0.1171239413 0.6203023544
#> [76] 0.0053674992 0.5467582649 0.4125465175 0.9685587775 0.0174874617
#> [81] 0.6833151839 0.8524390650 0.1601922255 0.1979631798 0.5681038106
#> [86] 0.2079392552 0.0616500510 0.1601922255 0.0122820336 0.6515622939
#> [91] 0.4348967301 0.5681038106 0.4945543530 0.1426349124 0.4841968094
#> [96] 0.9579177806 0.9473286354 0.2695379079 0.4236829779 0.1426349124
#> [101] 0.3372627837 0.7478885984 0.5891221739 0.0760868738 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 129 194 140 18 134 8 78 13 13.1 108 52 170 164
#> 23.41 22.40 12.68 15.21 17.81 18.43 23.88 14.34 14.34 18.29 10.42 19.54 23.60
#> 68 154 188 123 179 25 16 10 111 180 41 136 49
#> 20.62 12.63 16.16 13.00 18.63 6.32 8.71 10.53 17.45 14.82 18.02 21.83 12.19
#> 92 184 40 39 192 192.1 93 183 81 86 192.2 51 190
#> 22.92 17.77 18.00 15.59 16.44 16.44 10.33 9.24 14.06 23.81 16.44 18.23 20.81
#> 113 52.1 81.1 127 100 179.1 183.1 101 187 8.1 92.1 125 175
#> 22.86 10.42 14.06 3.53 16.07 18.63 9.24 9.97 9.92 18.43 22.92 15.65 21.91
#> 45 117 183.2 41.1 155 170.1 16.1 78.1 107 100.1 88 197 61
#> 17.42 17.46 9.24 18.02 13.08 19.54 8.71 23.88 11.18 16.07 18.37 21.60 10.12
#> 92.2 179.2 49.1 29 29.1 192.3 159 197.1 36 18.1 86.1 6 23
#> 22.92 18.63 12.19 15.45 15.45 16.44 10.55 21.60 21.19 15.21 23.81 15.64 16.92
#> 25.1 164.1 81.2 61.1 105 76 167 179.3 194.1 105.1 168 57 192.4
#> 6.32 23.60 14.06 10.12 19.75 19.22 15.55 18.63 22.40 19.75 23.72 14.46 16.44
#> 167.1 79 166 5 77 149 88.1 181 166.1 40.1 154.1 29.2 66
#> 15.55 16.23 19.98 16.43 7.27 8.37 18.37 16.46 19.98 18.00 12.63 15.45 22.13
#> 67 98 82 200 186 62 137 48 27 143 112 186.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 109 19 9 176 31 48.1 156 143.1 172 121 12 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 1 95 74 74.1 142 109.1 121.1 109.2 191 178 21 143.2 146
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 138 147 156.1 160 178.1 19.1 34 143.3 161 17 28 118
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185 112.1 46 46.1 28.1 147.1 94 102.1 122 173 121.2 67.1 11
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 185.1 152 84 2 19.2 38 12.1 109.3 144 176.1 200.1 165
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 146.1 47 104 33 120 74.2 104.1 143.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[67]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.005931783 0.517373840 0.447208851
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.2952241903 -0.0005747217 -0.4575329543
#> grade_iii, Cure model
#> 0.1375647893
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 18 15.21 1 49 1 0
#> 59 10.16 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 56 12.21 1 60 0 0
#> 194 22.40 1 38 0 1
#> 59.1 10.16 1 NA 1 0
#> 59.2 10.16 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 105 19.75 1 60 0 0
#> 14 12.89 1 21 0 0
#> 81 14.06 1 34 0 0
#> 189 10.51 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 60 13.15 1 38 1 0
#> 168 23.72 1 70 0 0
#> 24 23.89 1 38 0 0
#> 175 21.91 1 43 0 0
#> 113 22.86 1 34 0 0
#> 40 18.00 1 28 1 0
#> 128 20.35 1 35 0 1
#> 154 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 88 18.37 1 47 0 0
#> 42 12.43 1 49 0 1
#> 96 14.54 1 33 0 1
#> 56.1 12.21 1 60 0 0
#> 114 13.68 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 149 8.37 1 33 1 0
#> 134.1 17.81 1 47 1 0
#> 30 17.43 1 78 0 0
#> 18.1 15.21 1 49 1 0
#> 194.1 22.40 1 38 0 1
#> 81.1 14.06 1 34 0 0
#> 97 19.14 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 96.2 14.54 1 33 0 1
#> 113.1 22.86 1 34 0 0
#> 100 16.07 1 60 0 0
#> 36 21.19 1 48 0 1
#> 14.1 12.89 1 21 0 0
#> 40.1 18.00 1 28 1 0
#> 16 8.71 1 71 0 1
#> 100.1 16.07 1 60 0 0
#> 169 22.41 1 46 0 0
#> 157 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 60.1 13.15 1 38 1 0
#> 45 17.42 1 54 0 1
#> 40.2 18.00 1 28 1 0
#> 192 16.44 1 31 1 0
#> 139 21.49 1 63 1 0
#> 159 10.55 1 50 0 1
#> 85 16.44 1 36 0 0
#> 124 9.73 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 155 13.08 1 26 0 0
#> 69 23.23 1 25 0 1
#> 150 20.33 1 48 0 0
#> 69.1 23.23 1 25 0 1
#> 149.1 8.37 1 33 1 0
#> 177 12.53 1 75 0 0
#> 127 3.53 1 62 0 1
#> 59.3 10.16 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 14.2 12.89 1 21 0 0
#> 183 9.24 1 67 1 0
#> 52 10.42 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 134.2 17.81 1 47 1 0
#> 43 12.10 1 61 0 1
#> 32 20.90 1 37 1 0
#> 93 10.33 1 52 0 1
#> 52.1 10.42 1 52 0 1
#> 49 12.19 1 48 1 0
#> 128.1 20.35 1 35 0 1
#> 153 21.33 1 55 1 0
#> 5 16.43 1 51 0 1
#> 66 22.13 1 53 0 0
#> 39 15.59 1 37 0 1
#> 195.1 11.76 1 NA 1 0
#> 128.2 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 168.1 23.72 1 70 0 0
#> 197 21.60 1 69 1 0
#> 113.2 22.86 1 34 0 0
#> 91 5.33 1 61 0 1
#> 90 20.94 1 50 0 1
#> 140 12.68 1 59 1 0
#> 24.1 23.89 1 38 0 0
#> 42.1 12.43 1 49 0 1
#> 50 10.02 1 NA 1 0
#> 45.1 17.42 1 54 0 1
#> 184 17.77 1 38 0 0
#> 91.1 5.33 1 61 0 1
#> 153.1 21.33 1 55 1 0
#> 114.1 13.68 1 NA 0 0
#> 81.2 14.06 1 34 0 0
#> 45.2 17.42 1 54 0 1
#> 81.3 14.06 1 34 0 0
#> 76 19.22 1 54 0 1
#> 92 22.92 1 47 0 1
#> 183.1 9.24 1 67 1 0
#> 10 10.53 1 34 0 0
#> 189.1 10.51 1 NA 1 0
#> 192.1 16.44 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 29 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 77 7.27 1 67 0 1
#> 105.1 19.75 1 60 0 0
#> 104 24.00 0 50 1 0
#> 98 24.00 0 34 1 0
#> 31 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 200 24.00 0 64 0 0
#> 115 24.00 0 NA 1 0
#> 137 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 137.1 24.00 0 45 1 0
#> 46 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 35 24.00 0 51 0 0
#> 34 24.00 0 36 0 0
#> 104.1 24.00 0 50 1 0
#> 65 24.00 0 57 1 0
#> 44 24.00 0 56 0 0
#> 20 24.00 0 46 1 0
#> 7 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 3 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 22 24.00 0 52 1 0
#> 104.2 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 151 24.00 0 42 0 0
#> 193 24.00 0 45 0 1
#> 160.1 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 17.1 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 73 24.00 0 NA 0 1
#> 84.2 24.00 0 39 0 1
#> 21 24.00 0 47 0 0
#> 176 24.00 0 43 0 1
#> 2 24.00 0 9 0 0
#> 131 24.00 0 66 0 0
#> 163 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 116 24.00 0 58 0 1
#> 118 24.00 0 44 1 0
#> 193.1 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 138 24.00 0 44 1 0
#> 53 24.00 0 32 0 1
#> 120.1 24.00 0 68 0 1
#> 182 24.00 0 35 0 0
#> 38 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 172 24.00 0 41 0 0
#> 191 24.00 0 60 0 1
#> 118.1 24.00 0 44 1 0
#> 7.1 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 31.1 24.00 0 36 0 1
#> 12 24.00 0 63 0 0
#> 119 24.00 0 17 0 0
#> 118.2 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 118.3 24.00 0 44 1 0
#> 103.1 24.00 0 56 1 0
#> 67 24.00 0 25 0 0
#> 193.2 24.00 0 45 0 1
#> 141 24.00 0 44 1 0
#> 104.3 24.00 0 50 1 0
#> 176.1 24.00 0 43 0 1
#> 31.2 24.00 0 36 0 1
#> 151.1 24.00 0 42 0 0
#> 115.1 24.00 0 NA 1 0
#> 22.2 24.00 0 52 1 0
#> 46.1 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 185 24.00 0 44 1 0
#> 200.1 24.00 0 64 0 0
#> 141.1 24.00 0 44 1 0
#> 12.1 24.00 0 63 0 0
#> 165 24.00 0 47 0 0
#> 65.1 24.00 0 57 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.295 NA NA NA
#> 2 age, Cure model -0.000575 NA NA NA
#> 3 grade_ii, Cure model -0.458 NA NA NA
#> 4 grade_iii, Cure model 0.138 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00593 NA NA NA
#> 2 grade_ii, Survival model 0.517 NA NA NA
#> 3 grade_iii, Survival model 0.447 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.2952242 -0.0005747 -0.4575330 0.1375648
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 251 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.2952241903 -0.0005747217 -0.4575329543 0.1375647893
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.005931783 0.517373840 0.447208851
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.74111615 0.54368381 0.88416333 0.31248200 0.17071015 0.49520995
#> [7] 0.83356100 0.78814773 0.76158028 0.81419421 0.11894200 0.05354087
#> [13] 0.35628513 0.24865880 0.57131860 0.45487007 0.85913196 0.59695591
#> [19] 0.55298489 0.87178093 0.76838455 0.88416333 0.62952256 0.96137019
#> [25] 0.59695591 0.64557103 0.74111615 0.31248200 0.78814773 0.53434936
#> [31] 0.76838455 0.76838455 0.24865880 0.70536881 0.42103001 0.83356100
#> [37] 0.57131860 0.95568819 0.70536881 0.29604918 0.75475147 0.71981297
#> [43] 0.81419421 0.65349597 0.57131860 0.67604809 0.38444430 0.90866820
#> [49] 0.67604809 0.63758844 0.82709413 0.19395791 0.48501650 0.19395791
#> [55] 0.96137019 0.86546939 0.99457578 0.97256338 0.51504179 0.83356100
#> [61] 0.94426430 0.92071521 0.59695591 0.90259578 0.44390344 0.93254004
#> [67] 0.92071521 0.89647205 0.45487007 0.39745140 0.69804493 0.34162491
#> [73] 0.72699263 0.45487007 0.93842903 0.11894200 0.37077226 0.24865880
#> [79] 0.98368233 0.43263354 0.85275270 0.05354087 0.87178093 0.65349597
#> [85] 0.62132010 0.98368233 0.39745140 0.78814773 0.65349597 0.78814773
#> [91] 0.52479806 0.23093960 0.94426430 0.91469614 0.67604809 0.73410571
#> [97] 0.56223595 0.97814382 0.49520995 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 18 8 56 194 129 105 14 81 133 60 168 24 175
#> 15.21 18.43 12.21 22.40 23.41 19.75 12.89 14.06 14.65 13.15 23.72 23.89 21.91
#> 113 40 128 154 134 88 42 96 56.1 110 149 134.1 30
#> 22.86 18.00 20.35 12.63 17.81 18.37 12.43 14.54 12.21 17.56 8.37 17.81 17.43
#> 18.1 194.1 81.1 97 96.1 96.2 113.1 100 36 14.1 40.1 16 100.1
#> 15.21 22.40 14.06 19.14 14.54 14.54 22.86 16.07 21.19 12.89 18.00 8.71 16.07
#> 169 157 26 60.1 45 40.2 192 139 159 85 117 155 69
#> 22.41 15.10 15.77 13.15 17.42 18.00 16.44 21.49 10.55 16.44 17.46 13.08 23.23
#> 150 69.1 149.1 177 127 70 55 14.2 183 52 134.2 43 32
#> 20.33 23.23 8.37 12.53 3.53 7.38 19.34 12.89 9.24 10.42 17.81 12.10 20.90
#> 93 52.1 49 128.1 153 5 66 39 128.2 145 168.1 197 113.2
#> 10.33 10.42 12.19 20.35 21.33 16.43 22.13 15.59 20.35 10.07 23.72 21.60 22.86
#> 91 90 140 24.1 42.1 45.1 184 91.1 153.1 81.2 45.2 81.3 76
#> 5.33 20.94 12.68 23.89 12.43 17.42 17.77 5.33 21.33 14.06 17.42 14.06 19.22
#> 92 183.1 10 192.1 29 41 77 105.1 104 98 31 71 17
#> 22.92 9.24 10.53 16.44 15.45 18.02 7.27 19.75 24.00 24.00 24.00 24.00 24.00
#> 126 47 160 71.1 84 84.1 200 137 103 137.1 46 95 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 104.1 65 44 20 7 144 148 198 3 87 22 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 151 193 160.1 95.1 121 17.1 120 84.2 21 176 2 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 174 116 118 193.1 1 138 53 120.1 182 38 22.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 118.1 7.1 33 31.1 12 119 118.2 75 118.3 103.1 67 193.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 104.3 176.1 31.2 151.1 22.2 46.1 9 152 185 200.1 141.1 12.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 65.1
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[68]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003323101 0.718575331 0.563655200
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.56491573 0.01063098 -0.44458387
#> grade_iii, Cure model
#> 0.97322507
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 108 18.29 1 39 0 1
#> 164 23.60 1 76 0 1
#> 179 18.63 1 42 0 0
#> 91 5.33 1 61 0 1
#> 199 19.81 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 13 14.34 1 54 0 1
#> 26 15.77 1 49 0 1
#> 70 7.38 1 30 1 0
#> 86 23.81 1 58 0 1
#> 51 18.23 1 83 0 1
#> 107 11.18 1 54 1 0
#> 90 20.94 1 50 0 1
#> 164.1 23.60 1 76 0 1
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 155 13.08 1 26 0 0
#> 157.1 15.10 1 47 0 0
#> 63 22.77 1 31 1 0
#> 105 19.75 1 60 0 0
#> 59 10.16 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 59.1 10.16 1 NA 1 0
#> 39 15.59 1 37 0 1
#> 179.1 18.63 1 42 0 0
#> 190 20.81 1 42 1 0
#> 79 16.23 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 128 20.35 1 35 0 1
#> 189 10.51 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 69 23.23 1 25 0 1
#> 189.1 10.51 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 32 20.90 1 37 1 0
#> 78 23.88 1 43 0 0
#> 23 16.92 1 61 0 0
#> 189.2 10.51 1 NA 1 0
#> 127 3.53 1 62 0 1
#> 197 21.60 1 69 1 0
#> 8 18.43 1 32 0 0
#> 194.1 22.40 1 38 0 1
#> 130 16.47 1 53 0 1
#> 5 16.43 1 51 0 1
#> 130.1 16.47 1 53 0 1
#> 157.2 15.10 1 47 0 0
#> 15 22.68 1 48 0 0
#> 101 9.97 1 10 0 1
#> 150 20.33 1 48 0 0
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 42 12.43 1 49 0 1
#> 39.1 15.59 1 37 0 1
#> 197.1 21.60 1 69 1 0
#> 101.1 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 181 16.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 78.1 23.88 1 43 0 0
#> 24 23.89 1 38 0 0
#> 78.2 23.88 1 43 0 0
#> 8.1 18.43 1 32 0 0
#> 180 14.82 1 37 0 0
#> 51.1 18.23 1 83 0 1
#> 10 10.53 1 34 0 0
#> 114 13.68 1 NA 0 0
#> 105.1 19.75 1 60 0 0
#> 195 11.76 1 NA 1 0
#> 195.1 11.76 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 30 17.43 1 78 0 0
#> 86.1 23.81 1 58 0 1
#> 197.2 21.60 1 69 1 0
#> 125 15.65 1 67 1 0
#> 125.1 15.65 1 67 1 0
#> 100 16.07 1 60 0 0
#> 125.2 15.65 1 67 1 0
#> 59.2 10.16 1 NA 1 0
#> 69.1 23.23 1 25 0 1
#> 106 16.67 1 49 1 0
#> 93 10.33 1 52 0 1
#> 43.1 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 50 10.02 1 NA 1 0
#> 99 21.19 1 38 0 1
#> 179.2 18.63 1 42 0 0
#> 114.1 13.68 1 NA 0 0
#> 199.1 19.81 1 NA 0 1
#> 184 17.77 1 38 0 0
#> 57 14.46 1 45 0 1
#> 197.3 21.60 1 69 1 0
#> 179.3 18.63 1 42 0 0
#> 24.1 23.89 1 38 0 0
#> 88 18.37 1 47 0 0
#> 105.2 19.75 1 60 0 0
#> 117 17.46 1 26 0 1
#> 197.4 21.60 1 69 1 0
#> 101.2 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 107.1 11.18 1 54 1 0
#> 133 14.65 1 57 0 0
#> 175 21.91 1 43 0 0
#> 108.1 18.29 1 39 0 1
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 59.3 10.16 1 NA 1 0
#> 57.1 14.46 1 45 0 1
#> 106.1 16.67 1 49 1 0
#> 78.3 23.88 1 43 0 0
#> 181.1 16.46 1 45 0 1
#> 113 22.86 1 34 0 0
#> 146 24.00 0 63 1 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 65 24.00 0 57 1 0
#> 2 24.00 0 9 0 0
#> 152.1 24.00 0 36 0 1
#> 126 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 75 24.00 0 21 1 0
#> 2.1 24.00 0 9 0 0
#> 19 24.00 0 57 0 1
#> 67 24.00 0 25 0 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 35 24.00 0 51 0 0
#> 165 24.00 0 47 0 0
#> 138 24.00 0 44 1 0
#> 22 24.00 0 52 1 0
#> 116 24.00 0 58 0 1
#> 74 24.00 0 43 0 1
#> 176 24.00 0 43 0 1
#> 116.1 24.00 0 58 0 1
#> 198 24.00 0 66 0 1
#> 109 24.00 0 48 0 0
#> 147 24.00 0 76 1 0
#> 135 24.00 0 58 1 0
#> 135.1 24.00 0 58 1 0
#> 191 24.00 0 60 0 1
#> 67.1 24.00 0 25 0 0
#> 119.1 24.00 0 17 0 0
#> 143 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 161 24.00 0 45 0 0
#> 12 24.00 0 63 0 0
#> 82 24.00 0 34 0 0
#> 94 24.00 0 51 0 1
#> 163 24.00 0 66 0 0
#> 163.1 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 44 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#> 109.1 24.00 0 48 0 0
#> 12.1 24.00 0 63 0 0
#> 156 24.00 0 50 1 0
#> 65.1 24.00 0 57 1 0
#> 9 24.00 0 31 1 0
#> 152.2 24.00 0 36 0 1
#> 33 24.00 0 53 0 0
#> 44.1 24.00 0 56 0 0
#> 176.1 24.00 0 43 0 1
#> 138.1 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 122 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 147.1 24.00 0 76 1 0
#> 27.1 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 22.1 24.00 0 52 1 0
#> 2.2 24.00 0 9 0 0
#> 162.1 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 104 24.00 0 50 1 0
#> 196 24.00 0 19 0 0
#> 74.1 24.00 0 43 0 1
#> 116.2 24.00 0 58 0 1
#> 162.2 24.00 0 51 0 0
#> 163.2 24.00 0 66 0 0
#> 135.2 24.00 0 58 1 0
#> 1 24.00 0 23 1 0
#> 33.1 24.00 0 53 0 0
#> 7 24.00 0 37 1 0
#> 54.1 24.00 0 53 1 0
#> 104.1 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 132 24.00 0 55 0 0
#> 122.1 24.00 0 66 0 0
#> 119.2 24.00 0 17 0 0
#> 141 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 2.3 24.00 0 9 0 0
#> 116.3 24.00 0 58 0 1
#> 9.1 24.00 0 31 1 0
#> 148 24.00 0 61 1 0
#> 163.3 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 82.1 24.00 0 34 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.565 NA NA NA
#> 2 age, Cure model 0.0106 NA NA NA
#> 3 grade_ii, Cure model -0.445 NA NA NA
#> 4 grade_iii, Cure model 0.973 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00332 NA NA NA
#> 2 grade_ii, Survival model 0.719 NA NA NA
#> 3 grade_iii, Survival model 0.564 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.56492 0.01063 -0.44458 0.97323
#>
#> Degrees of Freedom: 185 Total (i.e. Null); 182 Residual
#> Null Deviance: 257.3
#> Residual Deviance: 243 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.56491573 0.01063098 -0.44458387 0.97322507
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003323101 0.718575331 0.563655200
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.53419679 0.15266875 0.46592094 0.98454840 0.88075570 0.83067113
#> [7] 0.71149664 0.96112345 0.10671014 0.55359935 0.89714829 0.36689571
#> [13] 0.15266875 0.77148836 0.69368395 0.84733429 0.77148836 0.23350260
#> [19] 0.42686352 0.25865710 0.74601774 0.46592094 0.38735101 0.68472947
#> [25] 0.83067113 0.40720846 0.76300657 0.18126068 0.97678313 0.37723621
#> [31] 0.04966579 0.61112555 0.99228713 0.30622015 0.50447105 0.25865710
#> [37] 0.63928620 0.67569054 0.63928620 0.77148836 0.24603240 0.92956455
#> [43] 0.41701891 0.85571409 0.95322553 0.87245344 0.74601774 0.30622015
#> [49] 0.92956455 0.45607910 0.65761758 0.20732830 0.04966579 0.01597011
#> [55] 0.04966579 0.50447105 0.79677434 0.55359935 0.91332963 0.42686352
#> [61] 0.59206078 0.60157592 0.10671014 0.30622015 0.72035843 0.72035843
#> [67] 0.70258009 0.72035843 0.18126068 0.62070264 0.92146419 0.88075570
#> [73] 0.96896614 0.39726285 0.35641100 0.46592094 0.57277782 0.81384992
#> [79] 0.30622015 0.46592094 0.01597011 0.52420679 0.42686352 0.58246810
#> [85] 0.30622015 0.92956455 0.13647914 0.89714829 0.80530432 0.29411180
#> [91] 0.53419679 0.28206952 0.86411204 0.81384992 0.62070264 0.04966579
#> [97] 0.65761758 0.22037383 0.00000000 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 108 164 179 91 43 13 26 70 86 51 107 90 164.1
#> 18.29 23.60 18.63 5.33 12.10 14.34 15.77 7.38 23.81 18.23 11.18 20.94 23.60
#> 157 188 155 157.1 63 105 194 39 179.1 190 79 13.1 128
#> 15.10 16.16 13.08 15.10 22.77 19.75 22.40 15.59 18.63 20.81 16.23 14.34 20.35
#> 29 69 25 32 78 23 127 197 8 194.1 130 5 130.1
#> 15.45 23.23 6.32 20.90 23.88 16.92 3.53 21.60 18.43 22.40 16.47 16.43 16.47
#> 157.2 15 101 150 177 149 42 39.1 197.1 101.1 170 181 92
#> 15.10 22.68 9.97 20.33 12.53 8.37 12.43 15.59 21.60 9.97 19.54 16.46 22.92
#> 78.1 24 78.2 8.1 180 51.1 10 105.1 111 30 86.1 197.2 125
#> 23.88 23.89 23.88 18.43 14.82 18.23 10.53 19.75 17.45 17.43 23.81 21.60 15.65
#> 125.1 100 125.2 69.1 106 93 43.1 77 68 99 179.2 184 57
#> 15.65 16.07 15.65 23.23 16.67 10.33 12.10 7.27 20.62 21.19 18.63 17.77 14.46
#> 197.3 179.3 24.1 88 105.2 117 197.4 101.2 168 107.1 133 175 108.1
#> 21.60 18.63 23.89 18.37 19.75 17.46 21.60 9.97 23.72 11.18 14.65 21.91 18.29
#> 66 37 57.1 106.1 78.3 181.1 113 146 152 28 65 2 152.1
#> 22.13 12.52 14.46 16.67 23.88 16.46 22.86 24.00 24.00 24.00 24.00 24.00 24.00
#> 126 71 75 2.1 19 67 27 119 35 165 138 22 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 176 116.1 198 109 147 135 135.1 191 67.1 119.1 143 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161 12 82 94 163 163.1 54 44 118 109.1 12.1 156 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 152.2 33 44.1 176.1 138.1 98 122 71.1 147.1 27.1 162 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 2.2 162.1 103 160 104 196 74.1 116.2 162.2 163.2 135.2 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 7 54.1 104.1 173 132 122.1 119.2 141 121 2.3 116.3 9.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 163.3 28.1 82.1
#> 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[69]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01095659 -0.01151266 -0.25872106
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.0782438 0.0141283 0.4074706
#> grade_iii, Cure model
#> 1.1126977
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 113 22.86 1 34 0 0
#> 29 15.45 1 68 1 0
#> 56 12.21 1 60 0 0
#> 157 15.10 1 47 0 0
#> 145 10.07 1 65 1 0
#> 171 16.57 1 41 0 1
#> 55 19.34 1 69 0 1
#> 159 10.55 1 50 0 1
#> 100 16.07 1 60 0 0
#> 134 17.81 1 47 1 0
#> 76 19.22 1 54 0 1
#> 130 16.47 1 53 0 1
#> 99 21.19 1 38 0 1
#> 90 20.94 1 50 0 1
#> 179 18.63 1 42 0 0
#> 77 7.27 1 67 0 1
#> 194 22.40 1 38 0 1
#> 192 16.44 1 31 1 0
#> 63 22.77 1 31 1 0
#> 30 17.43 1 78 0 0
#> 114 13.68 1 NA 0 0
#> 85 16.44 1 36 0 0
#> 93 10.33 1 52 0 1
#> 195 11.76 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 52 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 63.1 22.77 1 31 1 0
#> 149 8.37 1 33 1 0
#> 100.1 16.07 1 60 0 0
#> 167 15.55 1 56 1 0
#> 128 20.35 1 35 0 1
#> 59 10.16 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 16 8.71 1 71 0 1
#> 108 18.29 1 39 0 1
#> 183 9.24 1 67 1 0
#> 100.2 16.07 1 60 0 0
#> 57 14.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 51 18.23 1 83 0 1
#> 42 12.43 1 49 0 1
#> 140 12.68 1 59 1 0
#> 57.2 14.46 1 45 0 1
#> 88 18.37 1 47 0 0
#> 166 19.98 1 48 0 0
#> 197 21.60 1 69 1 0
#> 99.1 21.19 1 38 0 1
#> 8 18.43 1 32 0 0
#> 85.1 16.44 1 36 0 0
#> 195.1 11.76 1 NA 1 0
#> 149.1 8.37 1 33 1 0
#> 76.1 19.22 1 54 0 1
#> 195.2 11.76 1 NA 1 0
#> 110 17.56 1 65 0 1
#> 18 15.21 1 49 1 0
#> 150 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 130.1 16.47 1 53 0 1
#> 124 9.73 1 NA 1 0
#> 69 23.23 1 25 0 1
#> 90.1 20.94 1 50 0 1
#> 190 20.81 1 42 1 0
#> 149.2 8.37 1 33 1 0
#> 14.1 12.89 1 21 0 0
#> 159.1 10.55 1 50 0 1
#> 91 5.33 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 195.3 11.76 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 25 6.32 1 34 1 0
#> 76.2 19.22 1 54 0 1
#> 59.1 10.16 1 NA 1 0
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 14.2 12.89 1 21 0 0
#> 97.1 19.14 1 65 0 1
#> 18.1 15.21 1 49 1 0
#> 157.1 15.10 1 47 0 0
#> 86 23.81 1 58 0 1
#> 145.1 10.07 1 65 1 0
#> 129 23.41 1 53 1 0
#> 124.1 9.73 1 NA 1 0
#> 58 19.34 1 39 0 0
#> 25.1 6.32 1 34 1 0
#> 89 11.44 1 NA 0 0
#> 90.2 20.94 1 50 0 1
#> 177 12.53 1 75 0 0
#> 183.1 9.24 1 67 1 0
#> 25.2 6.32 1 34 1 0
#> 93.1 10.33 1 52 0 1
#> 101 9.97 1 10 0 1
#> 194.1 22.40 1 38 0 1
#> 158 20.14 1 74 1 0
#> 166.1 19.98 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 171.1 16.57 1 41 0 1
#> 51.1 18.23 1 83 0 1
#> 6 15.64 1 39 0 0
#> 128.1 20.35 1 35 0 1
#> 92 22.92 1 47 0 1
#> 55.1 19.34 1 69 0 1
#> 91.2 5.33 1 61 0 1
#> 190.1 20.81 1 42 1 0
#> 181 16.46 1 45 0 1
#> 127 3.53 1 62 0 1
#> 158.1 20.14 1 74 1 0
#> 69.1 23.23 1 25 0 1
#> 50 10.02 1 NA 1 0
#> 127.1 3.53 1 62 0 1
#> 149.3 8.37 1 33 1 0
#> 148 24.00 0 61 1 0
#> 121 24.00 0 57 1 0
#> 19 24.00 0 57 0 1
#> 83 24.00 0 6 0 0
#> 35 24.00 0 51 0 0
#> 47 24.00 0 38 0 1
#> 122 24.00 0 66 0 0
#> 48 24.00 0 31 1 0
#> 94 24.00 0 51 0 1
#> 35.1 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 103 24.00 0 56 1 0
#> 119 24.00 0 17 0 0
#> 95 24.00 0 68 0 1
#> 193 24.00 0 45 0 1
#> 65 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 53 24.00 0 32 0 1
#> 54 24.00 0 53 1 0
#> 33 24.00 0 53 0 0
#> 71 24.00 0 51 0 0
#> 103.1 24.00 0 56 1 0
#> 135 24.00 0 58 1 0
#> 7 24.00 0 37 1 0
#> 9 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 116 24.00 0 58 0 1
#> 46 24.00 0 71 0 0
#> 62 24.00 0 71 0 0
#> 83.1 24.00 0 6 0 0
#> 54.1 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 119.1 24.00 0 17 0 0
#> 173 24.00 0 19 0 1
#> 137.1 24.00 0 45 1 0
#> 196 24.00 0 19 0 0
#> 47.1 24.00 0 38 0 1
#> 122.1 24.00 0 66 0 0
#> 67 24.00 0 25 0 0
#> 131 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 7.1 24.00 0 37 1 0
#> 173.1 24.00 0 19 0 1
#> 112 24.00 0 61 0 0
#> 65.1 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 53.1 24.00 0 32 0 1
#> 19.1 24.00 0 57 0 1
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 165 24.00 0 47 0 0
#> 12 24.00 0 63 0 0
#> 17 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 22 24.00 0 52 1 0
#> 17.1 24.00 0 38 0 1
#> 141 24.00 0 44 1 0
#> 94.1 24.00 0 51 0 1
#> 172 24.00 0 41 0 0
#> 141.1 24.00 0 44 1 0
#> 1 24.00 0 23 1 0
#> 82 24.00 0 34 0 0
#> 9.1 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 94.2 24.00 0 51 0 1
#> 73 24.00 0 NA 0 1
#> 72.1 24.00 0 40 0 1
#> 161 24.00 0 45 0 0
#> 142 24.00 0 53 0 0
#> 163 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 33.1 24.00 0 53 0 0
#> 54.2 24.00 0 53 1 0
#> 165.1 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 160.1 24.00 0 31 1 0
#> 87.1 24.00 0 27 0 0
#> 178 24.00 0 52 1 0
#> 33.2 24.00 0 53 0 0
#> 200.1 24.00 0 64 0 0
#> 162 24.00 0 51 0 0
#> 191.1 24.00 0 60 0 1
#> 22.1 24.00 0 52 1 0
#> 142.1 24.00 0 53 0 0
#> 17.2 24.00 0 38 0 1
#> 156 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.08 NA NA NA
#> 2 age, Cure model 0.0141 NA NA NA
#> 3 grade_ii, Cure model 0.407 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0110 NA NA NA
#> 2 grade_ii, Survival model -0.0115 NA NA NA
#> 3 grade_iii, Survival model -0.259 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.07824 0.01413 0.40747 1.11270
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258.3
#> Residual Deviance: 246.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.0782438 0.0141283 0.4074706 1.1126977
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01095659 -0.01151266 -0.25872106
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.13741931 0.71138845 0.82368981 0.73459959 0.87336507 0.60426032
#> [7] 0.43580741 0.83805283 0.67153537 0.56896633 0.46547816 0.62137692
#> [13] 0.24667217 0.28541995 0.51347859 0.94109828 0.20313730 0.64681299
#> [19] 0.15572023 0.59558863 0.64681299 0.85931939 0.18747994 0.85222514
#> [25] 0.24667217 0.15572023 0.91453907 0.67153537 0.70345141 0.34663632
#> [31] 0.49442093 0.90774206 0.54176720 0.89412983 0.67153537 0.74975486
#> [37] 0.74975486 0.77219381 0.55106897 0.81642480 0.79446538 0.74975486
#> [43] 0.53243601 0.40423647 0.23251107 0.24667217 0.52299337 0.64681299
#> [49] 0.91453907 0.46547816 0.57789389 0.71923078 0.37056137 0.83089572
#> [55] 0.62137692 0.08061680 0.28541995 0.32249059 0.91453907 0.77219381
#> [61] 0.83805283 0.96750618 0.96750618 0.94778054 0.46547816 0.42523683
#> [67] 0.58674303 0.77219381 0.49442093 0.71923078 0.73459959 0.02976968
#> [73] 0.87336507 0.05912007 0.43580741 0.94778054 0.28541995 0.80913900
#> [79] 0.89412983 0.94778054 0.85931939 0.88718515 0.20313730 0.38245345
#> [85] 0.40423647 0.79446538 0.60426032 0.55106897 0.69543972 0.34663632
#> [91] 0.11795423 0.43580741 0.96750618 0.32249059 0.63831631 0.98703033
#> [97] 0.38245345 0.08061680 0.98703033 0.91453907 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 113 29 56 157 145 171 55 159 100 134 76 130 99
#> 22.86 15.45 12.21 15.10 10.07 16.57 19.34 10.55 16.07 17.81 19.22 16.47 21.19
#> 90 179 77 194 192 63 30 85 93 15 52 36 63.1
#> 20.94 18.63 7.27 22.40 16.44 22.77 17.43 16.44 10.33 22.68 10.42 21.19 22.77
#> 149 100.1 167 128 97 16 108 183 100.2 57 57.1 14 51
#> 8.37 16.07 15.55 20.35 19.14 8.71 18.29 9.24 16.07 14.46 14.46 12.89 18.23
#> 42 140 57.2 88 166 197 99.1 8 85.1 149.1 76.1 110 18
#> 12.43 12.68 14.46 18.37 19.98 21.60 21.19 18.43 16.44 8.37 19.22 17.56 15.21
#> 150 107 130.1 69 90.1 190 149.2 14.1 159.1 91 91.1 25 76.2
#> 20.33 11.18 16.47 23.23 20.94 20.81 8.37 12.89 10.55 5.33 5.33 6.32 19.22
#> 170 117 14.2 97.1 18.1 157.1 86 145.1 129 58 25.1 90.2 177
#> 19.54 17.46 12.89 19.14 15.21 15.10 23.81 10.07 23.41 19.34 6.32 20.94 12.53
#> 183.1 25.2 93.1 101 194.1 158 166.1 140.1 171.1 51.1 6 128.1 92
#> 9.24 6.32 10.33 9.97 22.40 20.14 19.98 12.68 16.57 18.23 15.64 20.35 22.92
#> 55.1 91.2 190.1 181 127 158.1 69.1 127.1 149.3 148 121 19 83
#> 19.34 5.33 20.81 16.46 3.53 20.14 23.23 3.53 8.37 24.00 24.00 24.00 24.00
#> 35 47 122 48 94 35.1 38 103 119 95 193 65 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 54 33 71 103.1 135 7 9 160 151 116 46 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 83.1 54.1 126 119.1 173 137.1 196 47.1 122.1 67 131 186 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 173.1 112 65.1 191 53.1 19.1 31 132 165 12 17 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 17.1 141 94.1 172 141.1 1 82 9.1 95.1 94.2 72.1 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 163 87 33.1 54.2 165.1 200 160.1 87.1 178 33.2 200.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 22.1 142.1 17.2 156
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[70]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.001589324 0.714779214 0.629033887
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 1.08769592 -0.02306688 -0.02709405
#> grade_iii, Cure model
#> 0.60973651
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 13 14.34 1 54 0 1
#> 153 21.33 1 55 1 0
#> 113 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 154 12.63 1 20 1 0
#> 86 23.81 1 58 0 1
#> 90 20.94 1 50 0 1
#> 117 17.46 1 26 0 1
#> 100 16.07 1 60 0 0
#> 110 17.56 1 65 0 1
#> 181 16.46 1 45 0 1
#> 113.1 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 108 18.29 1 39 0 1
#> 40 18.00 1 28 1 0
#> 13.1 14.34 1 54 0 1
#> 32 20.90 1 37 1 0
#> 15 22.68 1 48 0 0
#> 41 18.02 1 40 1 0
#> 13.2 14.34 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 86.1 23.81 1 58 0 1
#> 13.3 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 13.4 14.34 1 54 0 1
#> 101 9.97 1 10 0 1
#> 49 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 24 23.89 1 38 0 0
#> 77 7.27 1 67 0 1
#> 171 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 57 14.46 1 45 0 1
#> 159 10.55 1 50 0 1
#> 157 15.10 1 47 0 0
#> 8 18.43 1 32 0 0
#> 49.1 12.19 1 48 1 0
#> 107 11.18 1 54 1 0
#> 6 15.64 1 39 0 0
#> 150 20.33 1 48 0 0
#> 79 16.23 1 54 1 0
#> 97 19.14 1 65 0 1
#> 101.1 9.97 1 10 0 1
#> 149 8.37 1 33 1 0
#> 155 13.08 1 26 0 0
#> 192 16.44 1 31 1 0
#> 25 6.32 1 34 1 0
#> 58.1 19.34 1 39 0 0
#> 42 12.43 1 49 0 1
#> 180 14.82 1 37 0 0
#> 26 15.77 1 49 0 1
#> 184 17.77 1 38 0 0
#> 171.1 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 100.1 16.07 1 60 0 0
#> 177 12.53 1 75 0 0
#> 117.1 17.46 1 26 0 1
#> 197 21.60 1 69 1 0
#> 130 16.47 1 53 0 1
#> 153.1 21.33 1 55 1 0
#> 66 22.13 1 53 0 0
#> 123 13.00 1 44 1 0
#> 26.1 15.77 1 49 0 1
#> 43 12.10 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 181.1 16.46 1 45 0 1
#> 57.1 14.46 1 45 0 1
#> 108.1 18.29 1 39 0 1
#> 92 22.92 1 47 0 1
#> 181.2 16.46 1 45 0 1
#> 128 20.35 1 35 0 1
#> 171.2 16.57 1 41 0 1
#> 39 15.59 1 37 0 1
#> 181.3 16.46 1 45 0 1
#> 194 22.40 1 38 0 1
#> 99 21.19 1 38 0 1
#> 81 14.06 1 34 0 0
#> 56 12.21 1 60 0 0
#> 93.1 10.33 1 52 0 1
#> 170 19.54 1 43 0 1
#> 25.1 6.32 1 34 1 0
#> 69 23.23 1 25 0 1
#> 60 13.15 1 38 1 0
#> 159.1 10.55 1 50 0 1
#> 140 12.68 1 59 1 0
#> 49.2 12.19 1 48 1 0
#> 45 17.42 1 54 0 1
#> 93.2 10.33 1 52 0 1
#> 68.1 20.62 1 44 0 0
#> 70 7.38 1 30 1 0
#> 153.2 21.33 1 55 1 0
#> 23 16.92 1 61 0 0
#> 101.2 9.97 1 10 0 1
#> 24.1 23.89 1 38 0 0
#> 195 11.76 1 NA 1 0
#> 49.3 12.19 1 48 1 0
#> 63.1 22.77 1 31 1 0
#> 187 9.92 1 39 1 0
#> 13.5 14.34 1 54 0 1
#> 41.1 18.02 1 40 1 0
#> 91 5.33 1 61 0 1
#> 170.1 19.54 1 43 0 1
#> 57.2 14.46 1 45 0 1
#> 194.1 22.40 1 38 0 1
#> 41.2 18.02 1 40 1 0
#> 13.6 14.34 1 54 0 1
#> 195.1 11.76 1 NA 1 0
#> 190 20.81 1 42 1 0
#> 78 23.88 1 43 0 0
#> 166 19.98 1 48 0 0
#> 109 24.00 0 48 0 0
#> 84 24.00 0 39 0 1
#> 165 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 122 24.00 0 66 0 0
#> 186 24.00 0 45 1 0
#> 102 24.00 0 49 0 0
#> 173 24.00 0 19 0 1
#> 72 24.00 0 40 0 1
#> 141 24.00 0 44 1 0
#> 142 24.00 0 53 0 0
#> 182 24.00 0 35 0 0
#> 84.1 24.00 0 39 0 1
#> 35 24.00 0 51 0 0
#> 119 24.00 0 17 0 0
#> 173.1 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 152 24.00 0 36 0 1
#> 122.1 24.00 0 66 0 0
#> 165.1 24.00 0 47 0 0
#> 156 24.00 0 50 1 0
#> 193 24.00 0 45 0 1
#> 115 24.00 0 NA 1 0
#> 135 24.00 0 58 1 0
#> 156.1 24.00 0 50 1 0
#> 47 24.00 0 38 0 1
#> 147 24.00 0 76 1 0
#> 132 24.00 0 55 0 0
#> 80 24.00 0 41 0 0
#> 152.1 24.00 0 36 0 1
#> 22 24.00 0 52 1 0
#> 118.1 24.00 0 44 1 0
#> 12 24.00 0 63 0 0
#> 62 24.00 0 71 0 0
#> 17 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 116 24.00 0 58 0 1
#> 185 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 116.1 24.00 0 58 0 1
#> 1 24.00 0 23 1 0
#> 119.1 24.00 0 17 0 0
#> 17.1 24.00 0 38 0 1
#> 146.1 24.00 0 63 1 0
#> 19 24.00 0 57 0 1
#> 46 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 156.2 24.00 0 50 1 0
#> 142.1 24.00 0 53 0 0
#> 84.2 24.00 0 39 0 1
#> 121 24.00 0 57 1 0
#> 87 24.00 0 27 0 0
#> 7 24.00 0 37 1 0
#> 19.1 24.00 0 57 0 1
#> 185.1 24.00 0 44 1 0
#> 115.1 24.00 0 NA 1 0
#> 132.1 24.00 0 55 0 0
#> 172 24.00 0 41 0 0
#> 104 24.00 0 50 1 0
#> 163 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 7.1 24.00 0 37 1 0
#> 94 24.00 0 51 0 1
#> 185.2 24.00 0 44 1 0
#> 137 24.00 0 45 1 0
#> 132.2 24.00 0 55 0 0
#> 142.2 24.00 0 53 0 0
#> 116.2 24.00 0 58 0 1
#> 22.1 24.00 0 52 1 0
#> 62.1 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 65.1 24.00 0 57 1 0
#> 191 24.00 0 60 0 1
#> 185.3 24.00 0 44 1 0
#> 103 24.00 0 56 1 0
#> 165.2 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 95.1 24.00 0 68 0 1
#> 80.1 24.00 0 41 0 0
#> 198 24.00 0 66 0 1
#> 152.2 24.00 0 36 0 1
#> 46.1 24.00 0 71 0 0
#> 173.2 24.00 0 19 0 1
#> 31 24.00 0 36 0 1
#> 17.2 24.00 0 38 0 1
#> 146.2 24.00 0 63 1 0
#> 198.1 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 1.09 NA NA NA
#> 2 age, Cure model -0.0231 NA NA NA
#> 3 grade_ii, Cure model -0.0271 NA NA NA
#> 4 grade_iii, Cure model 0.610 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00159 NA NA NA
#> 2 grade_ii, Survival model 0.715 NA NA NA
#> 3 grade_iii, Survival model 0.629 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 1.08770 -0.02307 -0.02709 0.60974
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 256.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 1.08769592 -0.02306688 -0.02709405 0.60973651
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.001589324 0.714779214 0.629033887
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.79302375 0.36156159 0.22015696 0.50223202 0.86436504 0.12459171
#> [7] 0.40470712 0.60498471 0.70709442 0.59694498 0.66550057 0.22015696
#> [13] 0.25269111 0.53868743 0.58062116 0.79302375 0.41521066 0.28104742
#> [19] 0.55608100 0.79302375 0.16380448 0.12459171 0.79302375 0.74756200
#> [25] 0.79302375 0.94807054 0.88767490 0.43533331 0.03554087 0.97956620
#> [31] 0.63602972 0.29554315 0.77392791 0.92110025 0.75415990 0.52962557
#> [37] 0.88767490 0.91555391 0.73416391 0.46456063 0.70021506 0.52055562
#> [43] 0.94807054 0.96913753 0.84652439 0.69325177 0.98473478 0.50223202
#> [49] 0.87606420 0.76075333 0.72075975 0.58878659 0.63602972 0.93202433
#> [55] 0.70709442 0.87021711 0.60498471 0.34901458 0.65813490 0.36156159
#> [61] 0.33586218 0.85252146 0.72075975 0.90996603 0.76734330 0.66550057
#> [67] 0.77392791 0.53868743 0.20309927 0.66550057 0.45488439 0.63602972
#> [73] 0.74089292 0.66550057 0.30998529 0.39391484 0.83447611 0.88187146
#> [79] 0.93202433 0.48386565 0.98473478 0.18444343 0.84052553 0.92110025
#> [85] 0.85846867 0.88767490 0.62056458 0.93202433 0.43533331 0.97436782
#> [91] 0.36156159 0.62830199 0.94807054 0.03554087 0.88767490 0.25269111
#> [97] 0.96387447 0.79302375 0.55608100 0.99492140 0.48386565 0.77392791
#> [103] 0.30998529 0.55608100 0.79302375 0.42541291 0.09111083 0.47422092
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 13 153 113 58 154 86 90 117 100 110 181 113.1 63
#> 14.34 21.33 22.86 19.34 12.63 23.81 20.94 17.46 16.07 17.56 16.46 22.86 22.77
#> 108 40 13.1 32 15 41 13.2 168 86.1 13.3 18 13.4 101
#> 18.29 18.00 14.34 20.90 22.68 18.02 14.34 23.72 23.81 14.34 15.21 14.34 9.97
#> 49 68 24 77 171 169 57 159 157 8 49.1 107 6
#> 12.19 20.62 23.89 7.27 16.57 22.41 14.46 10.55 15.10 18.43 12.19 11.18 15.64
#> 150 79 97 101.1 149 155 192 25 58.1 42 180 26 184
#> 20.33 16.23 19.14 9.97 8.37 13.08 16.44 6.32 19.34 12.43 14.82 15.77 17.77
#> 171.1 93 100.1 177 117.1 197 130 153.1 66 123 26.1 43 133
#> 16.57 10.33 16.07 12.53 17.46 21.60 16.47 21.33 22.13 13.00 15.77 12.10 14.65
#> 181.1 57.1 108.1 92 181.2 128 171.2 39 181.3 194 99 81 56
#> 16.46 14.46 18.29 22.92 16.46 20.35 16.57 15.59 16.46 22.40 21.19 14.06 12.21
#> 93.1 170 25.1 69 60 159.1 140 49.2 45 93.2 68.1 70 153.2
#> 10.33 19.54 6.32 23.23 13.15 10.55 12.68 12.19 17.42 10.33 20.62 7.38 21.33
#> 23 101.2 24.1 49.3 63.1 187 13.5 41.1 91 170.1 57.2 194.1 41.2
#> 16.92 9.97 23.89 12.19 22.77 9.92 14.34 18.02 5.33 19.54 14.46 22.40 18.02
#> 13.6 190 78 166 109 84 165 118 122 186 102 173 72
#> 14.34 20.81 23.88 19.98 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 142 182 84.1 35 119 173.1 146 95 152 122.1 165.1 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193 135 156.1 47 147 132 80 152.1 22 118.1 12 62 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65 116 185 143 116.1 1 119.1 17.1 146.1 19 46 44 156.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142.1 84.2 121 87 7 19.1 185.1 132.1 172 104 163 54 7.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94 185.2 137 132.2 142.2 116.2 22.1 62.1 65.1 191 185.3 103 165.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 95.1 80.1 198 152.2 46.1 173.2 31 17.2 146.2 198.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[71]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005748278 1.008700286 0.492568313
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.93893702 0.01213207 0.54507661
#> grade_iii, Cure model
#> 1.14897318
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 49 12.19 1 48 1 0
#> 42 12.43 1 49 0 1
#> 70 7.38 1 30 1 0
#> 5 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 79 16.23 1 54 1 0
#> 57 14.46 1 45 0 1
#> 125 15.65 1 67 1 0
#> 43 12.10 1 61 0 1
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 106.1 16.67 1 49 1 0
#> 192 16.44 1 31 1 0
#> 166 19.98 1 48 0 0
#> 113 22.86 1 34 0 0
#> 168 23.72 1 70 0 0
#> 97 19.14 1 65 0 1
#> 181 16.46 1 45 0 1
#> 145 10.07 1 65 1 0
#> 69 23.23 1 25 0 1
#> 194.1 22.40 1 38 0 1
#> 188 16.16 1 46 0 1
#> 107 11.18 1 54 1 0
#> 51 18.23 1 83 0 1
#> 107.1 11.18 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 81 14.06 1 34 0 0
#> 170 19.54 1 43 0 1
#> 105 19.75 1 60 0 0
#> 61 10.12 1 36 0 1
#> 57.1 14.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 187 9.92 1 39 1 0
#> 57.2 14.46 1 45 0 1
#> 16 8.71 1 71 0 1
#> 55 19.34 1 69 0 1
#> 187.1 9.92 1 39 1 0
#> 164 23.60 1 76 0 1
#> 125.1 15.65 1 67 1 0
#> 4 17.64 1 NA 0 1
#> 159 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 100 16.07 1 60 0 0
#> 91 5.33 1 61 0 1
#> 189 10.51 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 110 17.56 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 40 18.00 1 28 1 0
#> 187.2 9.92 1 39 1 0
#> 189.1 10.51 1 NA 1 0
#> 187.3 9.92 1 39 1 0
#> 4.1 17.64 1 NA 0 1
#> 68 20.62 1 44 0 0
#> 93 10.33 1 52 0 1
#> 29 15.45 1 68 1 0
#> 89 11.44 1 NA 0 0
#> 58 19.34 1 39 0 0
#> 136 21.83 1 43 0 1
#> 183 9.24 1 67 1 0
#> 88 18.37 1 47 0 0
#> 59 10.16 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 10 10.53 1 34 0 0
#> 76 19.22 1 54 0 1
#> 60 13.15 1 38 1 0
#> 29.1 15.45 1 68 1 0
#> 81.1 14.06 1 34 0 0
#> 139 21.49 1 63 1 0
#> 68.1 20.62 1 44 0 0
#> 128 20.35 1 35 0 1
#> 26.1 15.77 1 49 0 1
#> 42.1 12.43 1 49 0 1
#> 92.1 22.92 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 78 23.88 1 43 0 0
#> 23 16.92 1 61 0 0
#> 170.1 19.54 1 43 0 1
#> 180 14.82 1 37 0 0
#> 97.2 19.14 1 65 0 1
#> 100.1 16.07 1 60 0 0
#> 117 17.46 1 26 0 1
#> 45.1 17.42 1 54 0 1
#> 149 8.37 1 33 1 0
#> 125.2 15.65 1 67 1 0
#> 194.2 22.40 1 38 0 1
#> 166.2 19.98 1 48 0 0
#> 41 18.02 1 40 1 0
#> 41.1 18.02 1 40 1 0
#> 29.2 15.45 1 68 1 0
#> 113.1 22.86 1 34 0 0
#> 97.3 19.14 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 8 18.43 1 32 0 0
#> 96 14.54 1 33 0 1
#> 188.1 16.16 1 46 0 1
#> 129 23.41 1 53 1 0
#> 32 20.90 1 37 1 0
#> 101 9.97 1 10 0 1
#> 55.1 19.34 1 69 0 1
#> 164.1 23.60 1 76 0 1
#> 66 22.13 1 53 0 0
#> 197 21.60 1 69 1 0
#> 40.1 18.00 1 28 1 0
#> 76.1 19.22 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 43.1 12.10 1 61 0 1
#> 59.1 10.16 1 NA 1 0
#> 41.2 18.02 1 40 1 0
#> 5.1 16.43 1 51 0 1
#> 41.3 18.02 1 40 1 0
#> 25 6.32 1 34 1 0
#> 146 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 64 24.00 0 43 0 0
#> 174 24.00 0 49 1 0
#> 73 24.00 0 NA 0 1
#> 182 24.00 0 35 0 0
#> 46 24.00 0 71 0 0
#> 64.1 24.00 0 43 0 0
#> 28 24.00 0 67 1 0
#> 67 24.00 0 25 0 0
#> 74 24.00 0 43 0 1
#> 200 24.00 0 64 0 0
#> 185 24.00 0 44 1 0
#> 165 24.00 0 47 0 0
#> 9 24.00 0 31 1 0
#> 83 24.00 0 6 0 0
#> 54 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 116 24.00 0 58 0 1
#> 119 24.00 0 17 0 0
#> 176 24.00 0 43 0 1
#> 141 24.00 0 44 1 0
#> 83.1 24.00 0 6 0 0
#> 48 24.00 0 31 1 0
#> 174.1 24.00 0 49 1 0
#> 94 24.00 0 51 0 1
#> 47 24.00 0 38 0 1
#> 80 24.00 0 41 0 0
#> 174.2 24.00 0 49 1 0
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 46.1 24.00 0 71 0 0
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 83.2 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 53 24.00 0 32 0 1
#> 48.1 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 82 24.00 0 34 0 0
#> 9.1 24.00 0 31 1 0
#> 182.1 24.00 0 35 0 0
#> 147.1 24.00 0 76 1 0
#> 163 24.00 0 66 0 0
#> 83.3 24.00 0 6 0 0
#> 191 24.00 0 60 0 1
#> 7 24.00 0 37 1 0
#> 12 24.00 0 63 0 0
#> 72 24.00 0 40 0 1
#> 53.1 24.00 0 32 0 1
#> 11.2 24.00 0 42 0 1
#> 83.4 24.00 0 6 0 0
#> 191.1 24.00 0 60 0 1
#> 165.1 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 122 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 147.2 24.00 0 76 1 0
#> 21 24.00 0 47 0 0
#> 28.1 24.00 0 67 1 0
#> 138.1 24.00 0 44 1 0
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 196 24.00 0 19 0 0
#> 21.1 24.00 0 47 0 0
#> 64.2 24.00 0 43 0 0
#> 148 24.00 0 61 1 0
#> 135 24.00 0 58 1 0
#> 80.1 24.00 0 41 0 0
#> 172 24.00 0 41 0 0
#> 112 24.00 0 61 0 0
#> 7.1 24.00 0 37 1 0
#> 131 24.00 0 66 0 0
#> 178 24.00 0 52 1 0
#> 72.1 24.00 0 40 0 1
#> 35.1 24.00 0 51 0 0
#> 67.1 24.00 0 25 0 0
#> 35.2 24.00 0 51 0 0
#> 112.1 24.00 0 61 0 0
#> 191.2 24.00 0 60 0 1
#> 119.1 24.00 0 17 0 0
#> 94.1 24.00 0 51 0 1
#> 83.5 24.00 0 6 0 0
#> 7.2 24.00 0 37 1 0
#> 103 24.00 0 56 1 0
#> 115 24.00 0 NA 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.939 NA NA NA
#> 2 age, Cure model 0.0121 NA NA NA
#> 3 grade_ii, Cure model 0.545 NA NA NA
#> 4 grade_iii, Cure model 1.15 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00575 NA NA NA
#> 2 grade_ii, Survival model 1.01 NA NA NA
#> 3 grade_iii, Survival model 0.493 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93894 0.01213 0.54508 1.14897
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 249.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.93893702 0.01213207 0.54507661 1.14897318
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005748278 1.008700286 0.492568313
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.83342965 0.81804935 0.97255611 0.63253613 0.11457422 0.64950877
#> [7] 0.77141687 0.70801873 0.84107897 0.16445708 0.59774656 0.59774656
#> [13] 0.62394089 0.28770660 0.13911386 0.03498862 0.41436716 0.61518959
#> [19] 0.90855148 0.10080013 0.16445708 0.65793924 0.85626611 0.48630225
#> [25] 0.85626611 0.28770660 0.79466117 0.34065049 0.31900646 0.90108581
#> [31] 0.77141687 0.57075407 0.92334222 0.77141687 0.95850945 0.36191925
#> [37] 0.92334222 0.05453136 0.70801873 0.87118591 0.69134860 0.67458358
#> [43] 0.98634685 0.00536498 0.55251422 0.41436716 0.53432759 0.92334222
#> [49] 0.92334222 0.25620023 0.89359964 0.73214321 0.36191925 0.21092147
#> [55] 0.95144915 0.47569755 0.31900646 0.87866338 0.39335020 0.81028829
#> [61] 0.73214321 0.79466117 0.23461134 0.25620023 0.27715882 0.69134860
#> [67] 0.81804935 0.11457422 0.87866338 0.01861598 0.58867546 0.34065049
#> [73] 0.75560687 0.41436716 0.67458358 0.56166445 0.57075407 0.96556518
#> [79] 0.70801873 0.16445708 0.28770660 0.49690336 0.49690336 0.73214321
#> [85] 0.13911386 0.41436716 0.98634685 0.45483345 0.76352635 0.65793924
#> [91] 0.08619779 0.24569400 0.91596312 0.36191925 0.05453136 0.19861500
#> [97] 0.22303168 0.53432759 0.39335020 0.45483345 0.84107897 0.49690336
#> [103] 0.63253613 0.49690336 0.97948195 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 49 42 70 5 92 79 57 125 43 194 106 106.1 192
#> 12.19 12.43 7.38 16.43 22.92 16.23 14.46 15.65 12.10 22.40 16.67 16.67 16.44
#> 166 113 168 97 181 145 69 194.1 188 107 51 107.1 166.1
#> 19.98 22.86 23.72 19.14 16.46 10.07 23.23 22.40 16.16 11.18 18.23 11.18 19.98
#> 81 170 105 61 57.1 45 187 57.2 16 55 187.1 164 125.1
#> 14.06 19.54 19.75 10.12 14.46 17.42 9.92 14.46 8.71 19.34 9.92 23.60 15.65
#> 159 26 100 91 24 110 97.1 40 187.2 187.3 68 93 29
#> 10.55 15.77 16.07 5.33 23.89 17.56 19.14 18.00 9.92 9.92 20.62 10.33 15.45
#> 58 136 183 88 105.1 10 76 60 29.1 81.1 139 68.1 128
#> 19.34 21.83 9.24 18.37 19.75 10.53 19.22 13.15 15.45 14.06 21.49 20.62 20.35
#> 26.1 42.1 92.1 10.1 78 23 170.1 180 97.2 100.1 117 45.1 149
#> 15.77 12.43 22.92 10.53 23.88 16.92 19.54 14.82 19.14 16.07 17.46 17.42 8.37
#> 125.2 194.2 166.2 41 41.1 29.2 113.1 97.3 91.1 8 96 188.1 129
#> 15.65 22.40 19.98 18.02 18.02 15.45 22.86 19.14 5.33 18.43 14.54 16.16 23.41
#> 32 101 55.1 164.1 66 197 40.1 76.1 8.1 43.1 41.2 5.1 41.3
#> 20.90 9.97 19.34 23.60 22.13 21.60 18.00 19.22 18.43 12.10 18.02 16.43 18.02
#> 25 146 35 64 174 182 46 64.1 28 67 74 200 185
#> 6.32 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165 9 83 54 20 116 119 176 141 83.1 48 174.1 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 80 174.2 173 147 46.1 11 162 62 83.2 138 98 53
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 48.1 11.1 82 9.1 182.1 147.1 163 83.3 191 7 12 72 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.2 83.4 191.1 165.1 95 122 198 147.2 21 28.1 138.1 84 84.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 21.1 64.2 148 135 80.1 172 112 7.1 131 178 72.1 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67.1 35.2 112.1 191.2 119.1 94.1 83.5 7.2 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[72]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004364105 0.412438438 0.231812402
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.00520161 0.02046079 0.14473713
#> grade_iii, Cure model
#> 0.51381271
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 32 20.90 1 37 1 0
#> 25 6.32 1 34 1 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 197 21.60 1 69 1 0
#> 10 10.53 1 34 0 0
#> 110 17.56 1 65 0 1
#> 43 12.10 1 61 0 1
#> 192 16.44 1 31 1 0
#> 70 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 24 23.89 1 38 0 0
#> 197.1 21.60 1 69 1 0
#> 105 19.75 1 60 0 0
#> 45 17.42 1 54 0 1
#> 171 16.57 1 41 0 1
#> 128 20.35 1 35 0 1
#> 85 16.44 1 36 0 0
#> 123 13.00 1 44 1 0
#> 99 21.19 1 38 0 1
#> 91 5.33 1 61 0 1
#> 153 21.33 1 55 1 0
#> 16 8.71 1 71 0 1
#> 166 19.98 1 48 0 0
#> 100 16.07 1 60 0 0
#> 49 12.19 1 48 1 0
#> 6 15.64 1 39 0 0
#> 97 19.14 1 65 0 1
#> 68 20.62 1 44 0 0
#> 61 10.12 1 36 0 1
#> 4 17.64 1 NA 0 1
#> 60 13.15 1 38 1 0
#> 61.1 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 23 16.92 1 61 0 0
#> 169 22.41 1 46 0 0
#> 195 11.76 1 NA 1 0
#> 24.1 23.89 1 38 0 0
#> 50 10.02 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 32.1 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 190 20.81 1 42 1 0
#> 101 9.97 1 10 0 1
#> 155 13.08 1 26 0 0
#> 180 14.82 1 37 0 0
#> 125 15.65 1 67 1 0
#> 50.1 10.02 1 NA 1 0
#> 61.2 10.12 1 36 0 1
#> 107 11.18 1 54 1 0
#> 195.1 11.76 1 NA 1 0
#> 51.1 18.23 1 83 0 1
#> 100.2 16.07 1 60 0 0
#> 10.1 10.53 1 34 0 0
#> 68.1 20.62 1 44 0 0
#> 199 19.81 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 177 12.53 1 75 0 0
#> 10.2 10.53 1 34 0 0
#> 89.1 11.44 1 NA 0 0
#> 91.1 5.33 1 61 0 1
#> 61.3 10.12 1 36 0 1
#> 125.1 15.65 1 67 1 0
#> 77 7.27 1 67 0 1
#> 77.1 7.27 1 67 0 1
#> 128.1 20.35 1 35 0 1
#> 175 21.91 1 43 0 0
#> 130 16.47 1 53 0 1
#> 56 12.21 1 60 0 0
#> 105.1 19.75 1 60 0 0
#> 8 18.43 1 32 0 0
#> 86 23.81 1 58 0 1
#> 70.1 7.38 1 30 1 0
#> 188 16.16 1 46 0 1
#> 55 19.34 1 69 0 1
#> 40 18.00 1 28 1 0
#> 99.1 21.19 1 38 0 1
#> 184 17.77 1 38 0 0
#> 16.1 8.71 1 71 0 1
#> 58 19.34 1 39 0 0
#> 150 20.33 1 48 0 0
#> 43.1 12.10 1 61 0 1
#> 125.2 15.65 1 67 1 0
#> 154 12.63 1 20 1 0
#> 168 23.72 1 70 0 0
#> 23.1 16.92 1 61 0 0
#> 40.1 18.00 1 28 1 0
#> 171.1 16.57 1 41 0 1
#> 63 22.77 1 31 1 0
#> 149 8.37 1 33 1 0
#> 134 17.81 1 47 1 0
#> 51.2 18.23 1 83 0 1
#> 100.3 16.07 1 60 0 0
#> 52 10.42 1 52 0 1
#> 136.1 21.83 1 43 0 1
#> 134.1 17.81 1 47 1 0
#> 29 15.45 1 68 1 0
#> 194 22.40 1 38 0 1
#> 41 18.02 1 40 1 0
#> 61.4 10.12 1 36 0 1
#> 86.1 23.81 1 58 0 1
#> 192.1 16.44 1 31 1 0
#> 107.1 11.18 1 54 1 0
#> 180.1 14.82 1 37 0 0
#> 86.2 23.81 1 58 0 1
#> 88 18.37 1 47 0 0
#> 6.1 15.64 1 39 0 0
#> 164 23.60 1 76 0 1
#> 154.1 12.63 1 20 1 0
#> 114 13.68 1 NA 0 0
#> 124 9.73 1 NA 1 0
#> 2 24.00 0 9 0 0
#> 12 24.00 0 63 0 0
#> 193 24.00 0 45 0 1
#> 33 24.00 0 53 0 0
#> 126 24.00 0 48 0 0
#> 74 24.00 0 43 0 1
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 173 24.00 0 19 0 1
#> 71 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 174 24.00 0 49 1 0
#> 38 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 1 24.00 0 23 1 0
#> 98 24.00 0 34 1 0
#> 104 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 95 24.00 0 68 0 1
#> 186 24.00 0 45 1 0
#> 19 24.00 0 57 0 1
#> 94 24.00 0 51 0 1
#> 161 24.00 0 45 0 0
#> 151 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 47.2 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 98.1 24.00 0 34 1 0
#> 191 24.00 0 60 0 1
#> 64 24.00 0 43 0 0
#> 163 24.00 0 66 0 0
#> 137 24.00 0 45 1 0
#> 112 24.00 0 61 0 0
#> 80 24.00 0 41 0 0
#> 34 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 138 24.00 0 44 1 0
#> 87 24.00 0 27 0 0
#> 161.1 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 165.1 24.00 0 47 0 0
#> 47.3 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 9.1 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 126.1 24.00 0 48 0 0
#> 71.1 24.00 0 51 0 0
#> 34.1 24.00 0 36 0 0
#> 176 24.00 0 43 0 1
#> 33.1 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 191.1 24.00 0 60 0 1
#> 143 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 2.1 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 137.1 24.00 0 45 1 0
#> 87.1 24.00 0 27 0 0
#> 84 24.00 0 39 0 1
#> 28 24.00 0 67 1 0
#> 174.1 24.00 0 49 1 0
#> 103 24.00 0 56 1 0
#> 182.1 24.00 0 35 0 0
#> 142 24.00 0 53 0 0
#> 34.2 24.00 0 36 0 0
#> 34.3 24.00 0 36 0 0
#> 34.4 24.00 0 36 0 0
#> 27 24.00 0 63 1 0
#> 1.1 24.00 0 23 1 0
#> 9.2 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 191.2 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 156 24.00 0 50 1 0
#> 143.1 24.00 0 51 0 0
#> 141 24.00 0 44 1 0
#> 53.2 24.00 0 32 0 1
#> 120.1 24.00 0 68 0 1
#> 173.1 24.00 0 19 0 1
#> 94.1 24.00 0 51 0 1
#> 173.2 24.00 0 19 0 1
#> 174.2 24.00 0 49 1 0
#> 162 24.00 0 51 0 0
#> 135.1 24.00 0 58 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.01 NA NA NA
#> 2 age, Cure model 0.0205 NA NA NA
#> 3 grade_ii, Cure model 0.145 NA NA NA
#> 4 grade_iii, Cure model 0.514 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00436 NA NA NA
#> 2 grade_ii, Survival model 0.412 NA NA NA
#> 3 grade_iii, Survival model 0.232 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00520 0.02046 0.14474 0.51381
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262.4
#> Residual Deviance: 255.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.00520161 0.02046079 0.14473713 0.51381271
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004364105 0.412438438 0.231812402
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.19274255 0.97121937 0.12337677 0.31746603 0.14346259 0.80750690
#> [7] 0.44588267 0.75886597 0.51468211 0.93283521 0.67046155 0.00807558
#> [13] 0.14346259 0.27842993 0.45571140 0.48518443 0.24016319 0.51468211
#> [19] 0.70017848 0.17331052 0.98084015 0.16322758 0.90375875 0.26869056
#> [25] 0.55332693 0.74906643 0.62118894 0.32741806 0.22118715 0.84636597
#> [31] 0.68038902 0.84636597 0.79775106 0.46554095 0.09194233 0.00807558
#> [37] 0.55332693 0.19274255 0.35745097 0.21163331 0.89403648 0.69027614
#> [43] 0.65074317 0.59207040 0.84636597 0.77835546 0.35745097 0.55332693
#> [49] 0.80750690 0.22118715 0.07100314 0.72943949 0.80750690 0.98084015
#> [55] 0.84636597 0.59207040 0.95201591 0.95201591 0.24016319 0.11281099
#> [61] 0.50478492 0.73923795 0.27842993 0.33738542 0.02629093 0.93283521
#> [67] 0.54353833 0.29787633 0.39715850 0.17331052 0.43606489 0.90375875
#> [73] 0.29787633 0.25901748 0.75886597 0.59207040 0.71004641 0.05025019
#> [79] 0.46554095 0.39715850 0.48518443 0.08168570 0.92312984 0.41671620
#> [85] 0.35745097 0.55332693 0.83656584 0.12337677 0.41671620 0.64085319
#> [91] 0.10241242 0.38708719 0.84636597 0.02629093 0.51468211 0.77835546
#> [97] 0.65074317 0.02629093 0.34739132 0.62118894 0.06054017 0.71004641
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 32 25 136 76 197 10 110 43 192 70 57 24 197.1
#> 20.90 6.32 21.83 19.22 21.60 10.53 17.56 12.10 16.44 7.38 14.46 23.89 21.60
#> 105 45 171 128 85 123 99 91 153 16 166 100 49
#> 19.75 17.42 16.57 20.35 16.44 13.00 21.19 5.33 21.33 8.71 19.98 16.07 12.19
#> 6 97 68 61 60 61.1 159 23 169 24.1 100.1 32.1 51
#> 15.64 19.14 20.62 10.12 13.15 10.12 10.55 16.92 22.41 23.89 16.07 20.90 18.23
#> 190 101 155 180 125 61.2 107 51.1 100.2 10.1 68.1 113 177
#> 20.81 9.97 13.08 14.82 15.65 10.12 11.18 18.23 16.07 10.53 20.62 22.86 12.53
#> 10.2 91.1 61.3 125.1 77 77.1 128.1 175 130 56 105.1 8 86
#> 10.53 5.33 10.12 15.65 7.27 7.27 20.35 21.91 16.47 12.21 19.75 18.43 23.81
#> 70.1 188 55 40 99.1 184 16.1 58 150 43.1 125.2 154 168
#> 7.38 16.16 19.34 18.00 21.19 17.77 8.71 19.34 20.33 12.10 15.65 12.63 23.72
#> 23.1 40.1 171.1 63 149 134 51.2 100.3 52 136.1 134.1 29 194
#> 16.92 18.00 16.57 22.77 8.37 17.81 18.23 16.07 10.42 21.83 17.81 15.45 22.40
#> 41 61.4 86.1 192.1 107.1 180.1 86.2 88 6.1 164 154.1 2 12
#> 18.02 10.12 23.81 16.44 11.18 14.82 23.81 18.37 15.64 23.60 12.63 24.00 24.00
#> 193 33 126 74 47 182 173 71 47.1 120 165 174 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 1 98 104 7 95 186 19 94 161 151 35 47.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 98.1 191 64 163 137 112 80 34 178 9 138 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 186.1 165.1 47.3 53 9.1 119 126.1 71.1 34.1 176 33.1 65
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 102 191.1 143 35.1 2.1 109 137.1 87.1 84 28 174.1 103 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 34.2 34.3 34.4 27 1.1 9.2 53.1 191.2 3 156 143.1 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.2 120.1 173.1 94.1 173.2 174.2 162 135.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[73]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0003316884 0.6676939764 -0.0136376693
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.33454904 0.00243825 0.21885408
#> grade_iii, Cure model
#> 0.96263559
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 190 20.81 1 42 1 0
#> 24 23.89 1 38 0 0
#> 145 10.07 1 65 1 0
#> 168 23.72 1 70 0 0
#> 23 16.92 1 61 0 0
#> 18 15.21 1 49 1 0
#> 90 20.94 1 50 0 1
#> 92 22.92 1 47 0 1
#> 136 21.83 1 43 0 1
#> 106 16.67 1 49 1 0
#> 157 15.10 1 47 0 0
#> 107 11.18 1 54 1 0
#> 190.1 20.81 1 42 1 0
#> 6 15.64 1 39 0 0
#> 184 17.77 1 38 0 0
#> 51 18.23 1 83 0 1
#> 66 22.13 1 53 0 0
#> 181 16.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 40 18.00 1 28 1 0
#> 45 17.42 1 54 0 1
#> 60 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 128 20.35 1 35 0 1
#> 58 19.34 1 39 0 0
#> 13 14.34 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 188 16.16 1 46 0 1
#> 5 16.43 1 51 0 1
#> 40.1 18.00 1 28 1 0
#> 36 21.19 1 48 0 1
#> 10 10.53 1 34 0 0
#> 88 18.37 1 47 0 0
#> 154 12.63 1 20 1 0
#> 117 17.46 1 26 0 1
#> 68 20.62 1 44 0 0
#> 106.1 16.67 1 49 1 0
#> 79 16.23 1 54 1 0
#> 180 14.82 1 37 0 0
#> 60.1 13.15 1 38 1 0
#> 69 23.23 1 25 0 1
#> 76 19.22 1 54 0 1
#> 117.1 17.46 1 26 0 1
#> 180.1 14.82 1 37 0 0
#> 129 23.41 1 53 1 0
#> 92.1 22.92 1 47 0 1
#> 136.1 21.83 1 43 0 1
#> 187 9.92 1 39 1 0
#> 128.1 20.35 1 35 0 1
#> 171 16.57 1 41 0 1
#> 88.1 18.37 1 47 0 0
#> 70 7.38 1 30 1 0
#> 183 9.24 1 67 1 0
#> 56 12.21 1 60 0 0
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 175.1 21.91 1 43 0 0
#> 13.1 14.34 1 54 0 1
#> 195 11.76 1 NA 1 0
#> 136.2 21.83 1 43 0 1
#> 58.1 19.34 1 39 0 0
#> 134 17.81 1 47 1 0
#> 183.1 9.24 1 67 1 0
#> 56.1 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 139 21.49 1 63 1 0
#> 50 10.02 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 14 12.89 1 21 0 0
#> 55 19.34 1 69 0 1
#> 60.2 13.15 1 38 1 0
#> 97 19.14 1 65 0 1
#> 45.1 17.42 1 54 0 1
#> 127 3.53 1 62 0 1
#> 101 9.97 1 10 0 1
#> 52 10.42 1 52 0 1
#> 130 16.47 1 53 0 1
#> 133.1 14.65 1 57 0 0
#> 29 15.45 1 68 1 0
#> 108 18.29 1 39 0 1
#> 86 23.81 1 58 0 1
#> 177 12.53 1 75 0 0
#> 145.1 10.07 1 65 1 0
#> 114 13.68 1 NA 0 0
#> 61 10.12 1 36 0 1
#> 69.1 23.23 1 25 0 1
#> 181.1 16.46 1 45 0 1
#> 30.1 17.43 1 78 0 0
#> 101.1 9.97 1 10 0 1
#> 164 23.60 1 76 0 1
#> 108.1 18.29 1 39 0 1
#> 51.1 18.23 1 83 0 1
#> 195.1 11.76 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 37 12.52 1 57 1 0
#> 195.2 11.76 1 NA 1 0
#> 153.1 21.33 1 55 1 0
#> 49.1 12.19 1 48 1 0
#> 86.1 23.81 1 58 0 1
#> 93 10.33 1 52 0 1
#> 167 15.55 1 56 1 0
#> 69.2 23.23 1 25 0 1
#> 110 17.56 1 65 0 1
#> 61.1 10.12 1 36 0 1
#> 24.1 23.89 1 38 0 0
#> 192 16.44 1 31 1 0
#> 69.3 23.23 1 25 0 1
#> 6.1 15.64 1 39 0 0
#> 175.2 21.91 1 43 0 0
#> 101.2 9.97 1 10 0 1
#> 176 24.00 0 43 0 1
#> 131 24.00 0 66 0 0
#> 47 24.00 0 38 0 1
#> 95 24.00 0 68 0 1
#> 67 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 109 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 118 24.00 0 44 1 0
#> 146 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 151 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 132 24.00 0 55 0 0
#> 193 24.00 0 45 0 1
#> 116 24.00 0 58 0 1
#> 71 24.00 0 51 0 0
#> 120 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 131.1 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 98 24.00 0 34 1 0
#> 47.1 24.00 0 38 0 1
#> 21 24.00 0 47 0 0
#> 118.1 24.00 0 44 1 0
#> 102.1 24.00 0 49 0 0
#> 31 24.00 0 36 0 1
#> 21.1 24.00 0 47 0 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 163 24.00 0 66 0 0
#> 48.1 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 162 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 38 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 46 24.00 0 71 0 0
#> 152 24.00 0 36 0 1
#> 191 24.00 0 60 0 1
#> 31.1 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 20 24.00 0 46 1 0
#> 28.1 24.00 0 67 1 0
#> 11 24.00 0 42 0 1
#> 162.1 24.00 0 51 0 0
#> 87 24.00 0 27 0 0
#> 53 24.00 0 32 0 1
#> 102.2 24.00 0 49 0 0
#> 186 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 147 24.00 0 76 1 0
#> 38.1 24.00 0 31 1 0
#> 200 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 53.1 24.00 0 32 0 1
#> 162.2 24.00 0 51 0 0
#> 152.1 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 84.1 24.00 0 39 0 1
#> 118.2 24.00 0 44 1 0
#> 143 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 64 24.00 0 43 0 0
#> 7 24.00 0 37 1 0
#> 80.1 24.00 0 41 0 0
#> 21.2 24.00 0 47 0 0
#> 87.1 24.00 0 27 0 0
#> 137.1 24.00 0 45 1 0
#> 71.1 24.00 0 51 0 0
#> 9.1 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 135.1 24.00 0 58 1 0
#> 198 24.00 0 66 0 1
#> 151.1 24.00 0 42 0 0
#> 102.3 24.00 0 49 0 0
#> 174 24.00 0 49 1 0
#> 80.2 24.00 0 41 0 0
#> 65 24.00 0 57 1 0
#> 87.2 24.00 0 27 0 0
#> 84.2 24.00 0 39 0 1
#> 141 24.00 0 44 1 0
#> 28.2 24.00 0 67 1 0
#> 131.2 24.00 0 66 0 0
#> 1 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.335 NA NA NA
#> 2 age, Cure model 0.00244 NA NA NA
#> 3 grade_ii, Cure model 0.219 NA NA NA
#> 4 grade_iii, Cure model 0.963 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000332 NA NA NA
#> 2 grade_ii, Survival model 0.668 NA NA NA
#> 3 grade_iii, Survival model -0.0136 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.334549 0.002438 0.218854 0.962636
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 258.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.33454904 0.00243825 0.21885408 0.96263559
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0003316884 0.6676939764 -0.0136376693
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.31696556 0.01330574 0.92277433 0.06109032 0.58322355 0.71713123
#> [7] 0.29659047 0.14248394 0.22154761 0.59253408 0.72568248 0.87509891
#> [13] 0.31696556 0.68216730 0.50930203 0.46189767 0.17672302 0.62860063
#> [19] 0.48130995 0.56475699 0.78529397 0.18844002 0.54630921 0.34596369
#> [25] 0.36524163 0.76826418 0.29659047 0.75124612 0.67332521 0.65553875
#> [31] 0.48130995 0.28624350 0.88305210 0.42316140 0.81826932 0.52787739
#> [37] 0.33620047 0.59253408 0.66448644 0.73423530 0.78529397 0.10116077
#> [43] 0.39382047 0.52787739 0.73423530 0.08893695 0.14248394 0.22154761
#> [49] 0.96171202 0.34596369 0.61049467 0.42316140 0.98477078 0.96949292
#> [55] 0.84288894 0.41337672 0.26594463 0.18844002 0.76826418 0.22154761
#> [61] 0.36524163 0.50001936 0.96949292 0.84288894 0.85913262 0.25480103
#> [67] 0.16501983 0.80996135 0.36524163 0.78529397 0.40359450 0.56475699
#> [73] 0.99238441 0.93838456 0.89100610 0.61954562 0.75124612 0.70848530
#> [79] 0.44251836 0.03663043 0.82649900 0.92277433 0.90692056 0.10116077
#> [85] 0.62860063 0.54630921 0.93838456 0.07496075 0.44251836 0.46189767
#> [91] 0.83473071 0.26594463 0.85913262 0.03663043 0.89896226 0.69974269
#> [97] 0.10116077 0.51858683 0.90692056 0.01330574 0.64659474 0.10116077
#> [103] 0.68216730 0.18844002 0.93838456 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [193] 0.00000000
#>
#> $Time
#> 190 24 145 168 23 18 90 92 136 106 157 107 190.1
#> 20.81 23.89 10.07 23.72 16.92 15.21 20.94 22.92 21.83 16.67 15.10 11.18 20.81
#> 6 184 51 66 181 40 45 60 175 30 128 58 13
#> 15.64 17.77 18.23 22.13 16.46 18.00 17.42 13.15 21.91 17.43 20.35 19.34 14.34
#> 90.1 133 188 5 40.1 36 10 88 154 117 68 106.1 79
#> 20.94 14.65 16.16 16.43 18.00 21.19 10.53 18.37 12.63 17.46 20.62 16.67 16.23
#> 180 60.1 69 76 117.1 180.1 129 92.1 136.1 187 128.1 171 88.1
#> 14.82 13.15 23.23 19.22 17.46 14.82 23.41 22.92 21.83 9.92 20.35 16.57 18.37
#> 70 183 56 8 153 175.1 13.1 136.2 58.1 134 183.1 56.1 49
#> 7.38 9.24 12.21 18.43 21.33 21.91 14.34 21.83 19.34 17.81 9.24 12.21 12.19
#> 139 194 14 55 60.2 97 45.1 127 101 52 130 133.1 29
#> 21.49 22.40 12.89 19.34 13.15 19.14 17.42 3.53 9.97 10.42 16.47 14.65 15.45
#> 108 86 177 145.1 61 69.1 181.1 30.1 101.1 164 108.1 51.1 37
#> 18.29 23.81 12.53 10.07 10.12 23.23 16.46 17.43 9.97 23.60 18.29 18.23 12.52
#> 153.1 49.1 86.1 93 167 69.2 110 61.1 24.1 192 69.3 6.1 175.2
#> 21.33 12.19 23.81 10.33 15.55 23.23 17.56 10.12 23.89 16.44 23.23 15.64 21.91
#> 101.2 176 131 47 95 67 54 109 72 118 146 48 12
#> 9.97 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 102 132 193 116 71 120 138 131.1 22 98 47.1 21
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118.1 102.1 31 21.1 137 135 163 48.1 112 182 162 28 38
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 80 46 152 191 31.1 44 20 28.1 11 162.1 87 53 102.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 74 147 38.1 200 9 11.1 53.1 162.2 152.1 84 84.1 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 103 64 7 80.1 21.2 87.1 137.1 71.1 9.1 64.1 135.1 198
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 102.3 174 80.2 65 87.2 84.2 141 28.2 131.2 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[74]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003092245 0.816026568 0.303458661
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.23119872 0.02511740 0.03458585
#> grade_iii, Cure model
#> 0.93710565
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 51 18.23 1 83 0 1
#> 55 19.34 1 69 0 1
#> 127 3.53 1 62 0 1
#> 10 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 125 15.65 1 67 1 0
#> 45 17.42 1 54 0 1
#> 123 13.00 1 44 1 0
#> 187.1 9.92 1 39 1 0
#> 101 9.97 1 10 0 1
#> 189 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 51.1 18.23 1 83 0 1
#> 45.1 17.42 1 54 0 1
#> 90 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 192 16.44 1 31 1 0
#> 79 16.23 1 54 1 0
#> 78 23.88 1 43 0 0
#> 15.1 22.68 1 48 0 0
#> 78.1 23.88 1 43 0 0
#> 77 7.27 1 67 0 1
#> 40 18.00 1 28 1 0
#> 134 17.81 1 47 1 0
#> 117 17.46 1 26 0 1
#> 181 16.46 1 45 0 1
#> 177 12.53 1 75 0 0
#> 190 20.81 1 42 1 0
#> 86 23.81 1 58 0 1
#> 66 22.13 1 53 0 0
#> 133 14.65 1 57 0 0
#> 52 10.42 1 52 0 1
#> 108 18.29 1 39 0 1
#> 155 13.08 1 26 0 0
#> 88 18.37 1 47 0 0
#> 15.2 22.68 1 48 0 0
#> 55.1 19.34 1 69 0 1
#> 175 21.91 1 43 0 0
#> 30 17.43 1 78 0 0
#> 145 10.07 1 65 1 0
#> 159 10.55 1 50 0 1
#> 26 15.77 1 49 0 1
#> 43 12.10 1 61 0 1
#> 36 21.19 1 48 0 1
#> 149 8.37 1 33 1 0
#> 106 16.67 1 49 1 0
#> 61.1 10.12 1 36 0 1
#> 36.1 21.19 1 48 0 1
#> 52.1 10.42 1 52 0 1
#> 32 20.90 1 37 1 0
#> 41 18.02 1 40 1 0
#> 194 22.40 1 38 0 1
#> 90.1 20.94 1 50 0 1
#> 66.1 22.13 1 53 0 0
#> 61.2 10.12 1 36 0 1
#> 5 16.43 1 51 0 1
#> 79.1 16.23 1 54 1 0
#> 18 15.21 1 49 1 0
#> 51.2 18.23 1 83 0 1
#> 155.1 13.08 1 26 0 0
#> 96 14.54 1 33 0 1
#> 130 16.47 1 53 0 1
#> 194.1 22.40 1 38 0 1
#> 183 9.24 1 67 1 0
#> 124 9.73 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 59 10.16 1 NA 1 0
#> 194.2 22.40 1 38 0 1
#> 85 16.44 1 36 0 0
#> 167 15.55 1 56 1 0
#> 99 21.19 1 38 0 1
#> 30.1 17.43 1 78 0 0
#> 59.1 10.16 1 NA 1 0
#> 51.3 18.23 1 83 0 1
#> 99.1 21.19 1 38 0 1
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 23 16.92 1 61 0 0
#> 153 21.33 1 55 1 0
#> 124.1 9.73 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 107 11.18 1 54 1 0
#> 5.1 16.43 1 51 0 1
#> 26.1 15.77 1 49 0 1
#> 192.1 16.44 1 31 1 0
#> 179 18.63 1 42 0 0
#> 106.1 16.67 1 49 1 0
#> 114 13.68 1 NA 0 0
#> 179.1 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 197 21.60 1 69 1 0
#> 56 12.21 1 60 0 0
#> 177.1 12.53 1 75 0 0
#> 149.1 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 166 19.98 1 48 0 0
#> 99.2 21.19 1 38 0 1
#> 58 19.34 1 39 0 0
#> 192.2 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 60.1 13.15 1 38 1 0
#> 125.1 15.65 1 67 1 0
#> 184.1 17.77 1 38 0 0
#> 81.1 14.06 1 34 0 0
#> 124.2 9.73 1 NA 1 0
#> 155.2 13.08 1 26 0 0
#> 107.1 11.18 1 54 1 0
#> 179.2 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 52.2 10.42 1 52 0 1
#> 136 21.83 1 43 0 1
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 132 24.00 0 55 0 0
#> 53 24.00 0 32 0 1
#> 162 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 135 24.00 0 58 1 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 83 24.00 0 6 0 0
#> 144 24.00 0 28 0 1
#> 182 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 20 24.00 0 46 1 0
#> 132.1 24.00 0 55 0 0
#> 71 24.00 0 51 0 0
#> 172 24.00 0 41 0 0
#> 22 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 185 24.00 0 44 1 0
#> 174 24.00 0 49 1 0
#> 112 24.00 0 61 0 0
#> 74 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 160 24.00 0 31 1 0
#> 131 24.00 0 66 0 0
#> 28.1 24.00 0 67 1 0
#> 87 24.00 0 27 0 0
#> 160.1 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 53.1 24.00 0 32 0 1
#> 174.1 24.00 0 49 1 0
#> 12 24.00 0 63 0 0
#> 104 24.00 0 50 1 0
#> 186 24.00 0 45 1 0
#> 135.1 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 137 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 2 24.00 0 9 0 0
#> 74.1 24.00 0 43 0 1
#> 64 24.00 0 43 0 0
#> 73 24.00 0 NA 0 1
#> 138 24.00 0 44 1 0
#> 120 24.00 0 68 0 1
#> 53.2 24.00 0 32 0 1
#> 156 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 126 24.00 0 48 0 0
#> 53.3 24.00 0 32 0 1
#> 80 24.00 0 41 0 0
#> 176.1 24.00 0 43 0 1
#> 156.1 24.00 0 50 1 0
#> 9 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 103.1 24.00 0 56 1 0
#> 3 24.00 0 31 1 0
#> 131.1 24.00 0 66 0 0
#> 34.1 24.00 0 36 0 0
#> 83.1 24.00 0 6 0 0
#> 54 24.00 0 53 1 0
#> 165 24.00 0 47 0 0
#> 73.1 24.00 0 NA 0 1
#> 27 24.00 0 63 1 0
#> 71.2 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 109.1 24.00 0 48 0 0
#> 132.2 24.00 0 55 0 0
#> 141 24.00 0 44 1 0
#> 3.1 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 186.1 24.00 0 45 1 0
#> 152.1 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 173.1 24.00 0 19 0 1
#> 161.1 24.00 0 45 0 0
#> 38 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 109.2 24.00 0 48 0 0
#> 21 24.00 0 47 0 0
#> 27.1 24.00 0 63 1 0
#> 152.2 24.00 0 36 0 1
#> 172.1 24.00 0 41 0 0
#> 196 24.00 0 19 0 0
#> 196.1 24.00 0 19 0 0
#> 38.1 24.00 0 31 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.23 NA NA NA
#> 2 age, Cure model 0.0251 NA NA NA
#> 3 grade_ii, Cure model 0.0346 NA NA NA
#> 4 grade_iii, Cure model 0.937 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00309 NA NA NA
#> 2 grade_ii, Survival model 0.816 NA NA NA
#> 3 grade_iii, Survival model 0.303 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.23120 0.02512 0.03459 0.93711
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.3
#> Residual Deviance: 247.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.23119872 0.02511740 0.03458585 0.93710565
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003092245 0.816026568 0.303458661
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.68874243 0.40639341 0.32644521 0.99273210 0.86436007 0.94114998
#> [7] 0.67227496 0.52193790 0.80152769 0.94114998 0.93352188 0.05421795
#> [13] 0.40639341 0.52193790 0.26283082 0.90296068 0.58700799 0.63857860
#> [19] 0.01223077 0.05421795 0.01223077 0.98545791 0.45546362 0.46514394
#> [25] 0.49351181 0.57782754 0.80942131 0.29566694 0.03832746 0.13056036
#> [31] 0.72148946 0.87214937 0.39617915 0.77785448 0.38591179 0.05421795
#> [37] 0.32644521 0.15717549 0.50299622 0.92587420 0.85657777 0.65546230
#> [43] 0.83313275 0.21050983 0.96355820 0.55031289 0.90296068 0.21050983
#> [49] 0.87214937 0.28486270 0.44555720 0.09383397 0.26283082 0.13056036
#> [55] 0.90296068 0.62127697 0.63857860 0.70524411 0.40639341 0.77785448
#> [61] 0.72963196 0.56862098 0.09383397 0.95610186 0.30609549 0.09383397
#> [67] 0.58700799 0.69703731 0.21050983 0.50299622 0.40639341 0.21050983
#> [73] 0.89521532 0.76202862 0.54077967 0.19818582 0.73775423 0.84106134
#> [79] 0.62127697 0.65546230 0.58700799 0.35602665 0.55031289 0.35602665
#> [85] 0.47463552 0.18512504 0.82519496 0.80942131 0.96355820 0.74586345
#> [91] 0.31624776 0.21050983 0.32644521 0.58700799 0.71336179 0.76202862
#> [97] 0.67227496 0.47463552 0.74586345 0.77785448 0.84106134 0.35602665
#> [103] 0.97817829 0.87214937 0.17125588 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 6 51 55 127 10 187 125 45 123 187.1 101 15 51.1
#> 15.64 18.23 19.34 3.53 10.53 9.92 15.65 17.42 13.00 9.92 9.97 22.68 18.23
#> 45.1 90 61 192 79 78 15.1 78.1 77 40 134 117 181
#> 17.42 20.94 10.12 16.44 16.23 23.88 22.68 23.88 7.27 18.00 17.81 17.46 16.46
#> 177 190 86 66 133 52 108 155 88 15.2 55.1 175 30
#> 12.53 20.81 23.81 22.13 14.65 10.42 18.29 13.08 18.37 22.68 19.34 21.91 17.43
#> 145 159 26 43 36 149 106 61.1 36.1 52.1 32 41 194
#> 10.07 10.55 15.77 12.10 21.19 8.37 16.67 10.12 21.19 10.42 20.90 18.02 22.40
#> 90.1 66.1 61.2 5 79.1 18 51.2 155.1 96 130 194.1 183 158
#> 20.94 22.13 10.12 16.43 16.23 15.21 18.23 13.08 14.54 16.47 22.40 9.24 20.14
#> 194.2 85 167 99 30.1 51.3 99.1 93 60 23 153 13 107
#> 22.40 16.44 15.55 21.19 17.43 18.23 21.19 10.33 13.15 16.92 21.33 14.34 11.18
#> 5.1 26.1 192.1 179 106.1 179.1 184 197 56 177.1 149.1 81 166
#> 16.43 15.77 16.44 18.63 16.67 18.63 17.77 21.60 12.21 12.53 8.37 14.06 19.98
#> 99.2 58 192.2 180 60.1 125.1 184.1 81.1 155.2 107.1 179.2 70 52.2
#> 21.19 19.34 16.44 14.82 13.15 15.65 17.77 14.06 13.08 11.18 18.63 7.38 10.42
#> 136 103 34 132 53 162 72 135 152 28 83 144 182
#> 21.83 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 132.1 71 172 22 71.1 185 174 112 74 191 160 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 87 160.1 98 53.1 174.1 12 104 186 135.1 176 137 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 74.1 64 138 120 53.2 156 109 126 53.3 80 176.1 156.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 75 17 103.1 3 131.1 34.1 83.1 54 165 27 71.2 126.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 132.2 141 3.1 161 186.1 152.1 173 173.1 161.1 38 48 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.2 21 27.1 152.2 172.1 196 196.1 38.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[75]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006436871 0.600207192 0.634753687
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.15670491 0.01373777 0.61488883
#> grade_iii, Cure model
#> 1.46519997
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 107 11.18 1 54 1 0
#> 86 23.81 1 58 0 1
#> 190 20.81 1 42 1 0
#> 43 12.10 1 61 0 1
#> 42 12.43 1 49 0 1
#> 8 18.43 1 32 0 0
#> 140 12.68 1 59 1 0
#> 59 10.16 1 NA 1 0
#> 49 12.19 1 48 1 0
#> 199 19.81 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 63 22.77 1 31 1 0
#> 23 16.92 1 61 0 0
#> 89 11.44 1 NA 0 0
#> 43.1 12.10 1 61 0 1
#> 139 21.49 1 63 1 0
#> 170 19.54 1 43 0 1
#> 78 23.88 1 43 0 0
#> 93 10.33 1 52 0 1
#> 4.1 17.64 1 NA 0 1
#> 157 15.10 1 47 0 0
#> 183 9.24 1 67 1 0
#> 45 17.42 1 54 0 1
#> 26 15.77 1 49 0 1
#> 136 21.83 1 43 0 1
#> 187 9.92 1 39 1 0
#> 166 19.98 1 48 0 0
#> 134 17.81 1 47 1 0
#> 24 23.89 1 38 0 0
#> 105 19.75 1 60 0 0
#> 168 23.72 1 70 0 0
#> 37 12.52 1 57 1 0
#> 105.1 19.75 1 60 0 0
#> 153 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 167 15.55 1 56 1 0
#> 6 15.64 1 39 0 0
#> 91 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 77 7.27 1 67 0 1
#> 159 10.55 1 50 0 1
#> 10 10.53 1 34 0 0
#> 26.1 15.77 1 49 0 1
#> 25 6.32 1 34 1 0
#> 45.1 17.42 1 54 0 1
#> 150 20.33 1 48 0 0
#> 171 16.57 1 41 0 1
#> 169 22.41 1 46 0 0
#> 111 17.45 1 47 0 1
#> 100 16.07 1 60 0 0
#> 26.2 15.77 1 49 0 1
#> 168.1 23.72 1 70 0 0
#> 188 16.16 1 46 0 1
#> 97 19.14 1 65 0 1
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 128 20.35 1 35 0 1
#> 63.1 22.77 1 31 1 0
#> 113 22.86 1 34 0 0
#> 32 20.90 1 37 1 0
#> 111.1 17.45 1 47 0 1
#> 4.2 17.64 1 NA 0 1
#> 125 15.65 1 67 1 0
#> 57 14.46 1 45 0 1
#> 14 12.89 1 21 0 0
#> 170.1 19.54 1 43 0 1
#> 171.1 16.57 1 41 0 1
#> 89.1 11.44 1 NA 0 0
#> 25.1 6.32 1 34 1 0
#> 57.1 14.46 1 45 0 1
#> 189 10.51 1 NA 1 0
#> 136.1 21.83 1 43 0 1
#> 134.1 17.81 1 47 1 0
#> 158 20.14 1 74 1 0
#> 190.1 20.81 1 42 1 0
#> 133 14.65 1 57 0 0
#> 68 20.62 1 44 0 0
#> 183.1 9.24 1 67 1 0
#> 97.1 19.14 1 65 0 1
#> 52 10.42 1 52 0 1
#> 124 9.73 1 NA 1 0
#> 6.1 15.64 1 39 0 0
#> 128.1 20.35 1 35 0 1
#> 123.1 13.00 1 44 1 0
#> 155 13.08 1 26 0 0
#> 183.2 9.24 1 67 1 0
#> 52.1 10.42 1 52 0 1
#> 171.2 16.57 1 41 0 1
#> 199.1 19.81 1 NA 0 1
#> 68.1 20.62 1 44 0 0
#> 70 7.38 1 30 1 0
#> 43.2 12.10 1 61 0 1
#> 42.1 12.43 1 49 0 1
#> 158.1 20.14 1 74 1 0
#> 149 8.37 1 33 1 0
#> 124.1 9.73 1 NA 1 0
#> 92 22.92 1 47 0 1
#> 153.1 21.33 1 55 1 0
#> 145 10.07 1 65 1 0
#> 100.1 16.07 1 60 0 0
#> 16 8.71 1 71 0 1
#> 42.2 12.43 1 49 0 1
#> 13 14.34 1 54 0 1
#> 18 15.21 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 133.1 14.65 1 57 0 0
#> 189.1 10.51 1 NA 1 0
#> 88 18.37 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 183.3 9.24 1 67 1 0
#> 67 24.00 0 25 0 0
#> 54 24.00 0 53 1 0
#> 64 24.00 0 43 0 0
#> 132 24.00 0 55 0 0
#> 95 24.00 0 68 0 1
#> 165 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 104 24.00 0 50 1 0
#> 74 24.00 0 43 0 1
#> 12 24.00 0 63 0 0
#> 104.1 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 22 24.00 0 52 1 0
#> 48 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 67.1 24.00 0 25 0 0
#> 46 24.00 0 71 0 0
#> 120 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 28 24.00 0 67 1 0
#> 47 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 87 24.00 0 27 0 0
#> 151 24.00 0 42 0 0
#> 120.1 24.00 0 68 0 1
#> 141 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 186 24.00 0 45 1 0
#> 104.2 24.00 0 50 1 0
#> 7 24.00 0 37 1 0
#> 11 24.00 0 42 0 1
#> 137 24.00 0 45 1 0
#> 20 24.00 0 46 1 0
#> 74.1 24.00 0 43 0 1
#> 34 24.00 0 36 0 0
#> 186.1 24.00 0 45 1 0
#> 200 24.00 0 64 0 0
#> 27 24.00 0 63 1 0
#> 185 24.00 0 44 1 0
#> 73.1 24.00 0 NA 0 1
#> 3 24.00 0 31 1 0
#> 1 24.00 0 23 1 0
#> 34.1 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 148 24.00 0 61 1 0
#> 102 24.00 0 49 0 0
#> 20.1 24.00 0 46 1 0
#> 142 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 178 24.00 0 52 1 0
#> 28.1 24.00 0 67 1 0
#> 72 24.00 0 40 0 1
#> 200.1 24.00 0 64 0 0
#> 182 24.00 0 35 0 0
#> 143 24.00 0 51 0 0
#> 35.1 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 11.1 24.00 0 42 0 1
#> 143.1 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 9 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 35.2 24.00 0 51 0 0
#> 22.1 24.00 0 52 1 0
#> 162 24.00 0 51 0 0
#> 12.1 24.00 0 63 0 0
#> 119 24.00 0 17 0 0
#> 176 24.00 0 43 0 1
#> 67.2 24.00 0 25 0 0
#> 46.1 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 74.2 24.00 0 43 0 1
#> 119.1 24.00 0 17 0 0
#> 126 24.00 0 48 0 0
#> 34.2 24.00 0 36 0 0
#> 95.1 24.00 0 68 0 1
#> 46.2 24.00 0 71 0 0
#> 160 24.00 0 31 1 0
#> 200.2 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 98 24.00 0 34 1 0
#> 67.3 24.00 0 25 0 0
#> 20.2 24.00 0 46 1 0
#> 200.3 24.00 0 64 0 0
#> 198 24.00 0 66 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.16 NA NA NA
#> 2 age, Cure model 0.0137 NA NA NA
#> 3 grade_ii, Cure model 0.615 NA NA NA
#> 4 grade_iii, Cure model 1.47 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00644 NA NA NA
#> 2 grade_ii, Survival model 0.600 NA NA NA
#> 3 grade_iii, Survival model 0.635 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.15670 0.01374 0.61489 1.46520
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 255.6
#> Residual Deviance: 237.9 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.15670491 0.01373777 0.61488883 1.46519997
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006436871 0.600207192 0.634753687
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.91035746 0.16291902 0.45076722 0.89506208 0.87385323 0.61855679
#> [7] 0.86279915 0.88977119 0.59302926 0.72340827 0.29553957 0.69592936
#> [13] 0.89506208 0.39908601 0.57500402 0.11083521 0.93536601 0.80515650
#> [19] 0.94994339 0.68163759 0.75616177 0.35204238 0.94512136 0.54640491
#> [25] 0.64343348 0.05065448 0.55609687 0.19649693 0.86835486 0.55609687
#> [31] 0.41327738 0.38396232 0.79311762 0.78090723 0.99557326 0.63525142
#> [37] 0.98215438 0.91543952 0.92047676 0.75616177 0.98666859 0.68163759
#> [43] 0.51655921 0.70307684 0.33308652 0.66682704 0.74321098 0.75616177
#> [49] 0.19649693 0.73015294 0.60188485 0.84597763 0.65911260 0.49559900
#> [55] 0.29553957 0.27241313 0.43846029 0.66682704 0.77475040 0.82294513
#> [61] 0.85718324 0.57500402 0.70307684 0.98666859 0.82294513 0.35204238
#> [67] 0.64343348 0.52706985 0.45076722 0.81112630 0.47335674 0.94994339
#> [73] 0.60188485 0.92550726 0.78090723 0.49559900 0.84597763 0.84024808
#> [79] 0.94994339 0.92550726 0.70307684 0.47335674 0.97760031 0.89506208
#> [85] 0.87385323 0.52706985 0.97302042 0.24879775 0.41327738 0.94026607
#> [91] 0.74321098 0.96841334 0.87385323 0.83451141 0.79917103 0.73015294
#> [97] 0.81112630 0.62692373 0.94994339 0.00000000 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 107 86 190 43 42 8 140 49 76 181 63 23 43.1
#> 11.18 23.81 20.81 12.10 12.43 18.43 12.68 12.19 19.22 16.46 22.77 16.92 12.10
#> 139 170 78 93 157 183 45 26 136 187 166 134 24
#> 21.49 19.54 23.88 10.33 15.10 9.24 17.42 15.77 21.83 9.92 19.98 17.81 23.89
#> 105 168 37 105.1 153 197 167 6 91 41 77 159 10
#> 19.75 23.72 12.52 19.75 21.33 21.60 15.55 15.64 5.33 18.02 7.27 10.55 10.53
#> 26.1 25 45.1 150 171 169 111 100 26.2 168.1 188 97 123
#> 15.77 6.32 17.42 20.33 16.57 22.41 17.45 16.07 15.77 23.72 16.16 19.14 13.00
#> 110 128 63.1 113 32 111.1 125 57 14 170.1 171.1 25.1 57.1
#> 17.56 20.35 22.77 22.86 20.90 17.45 15.65 14.46 12.89 19.54 16.57 6.32 14.46
#> 136.1 134.1 158 190.1 133 68 183.1 97.1 52 6.1 128.1 123.1 155
#> 21.83 17.81 20.14 20.81 14.65 20.62 9.24 19.14 10.42 15.64 20.35 13.00 13.08
#> 183.2 52.1 171.2 68.1 70 43.2 42.1 158.1 149 92 153.1 145 100.1
#> 9.24 10.42 16.57 20.62 7.38 12.10 12.43 20.14 8.37 22.92 21.33 10.07 16.07
#> 16 42.2 13 18 188.1 133.1 88 183.3 67 54 64 132 95
#> 8.71 12.43 14.34 15.21 16.16 14.65 18.37 9.24 24.00 24.00 24.00 24.00 24.00
#> 165 103 35 104 74 12 104.1 33 22 48 174 67.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 83 28 47 193 163 87 151 120.1 141 19 186 104.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7 11 137 20 74.1 34 186.1 200 27 185 3 1 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 148 102 20.1 142 142.1 178 28.1 72 200.1 182 143 35.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2 11.1 143.1 138 9 21 35.2 22.1 162 12.1 119 176 67.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 82 74.2 119.1 126 34.2 95.1 46.2 160 200.2 196 98 67.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20.2 200.3 198
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[76]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.006322386 0.242431082 0.125409850
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.181030463 0.009838417 -0.651155188
#> grade_iii, Cure model
#> 0.400757375
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 134 17.81 1 47 1 0
#> 23 16.92 1 61 0 0
#> 154 12.63 1 20 1 0
#> 36 21.19 1 48 0 1
#> 6 15.64 1 39 0 0
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 189 10.51 1 NA 1 0
#> 133 14.65 1 57 0 0
#> 13 14.34 1 54 0 1
#> 105 19.75 1 60 0 0
#> 41 18.02 1 40 1 0
#> 180 14.82 1 37 0 0
#> 159 10.55 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 159.1 10.55 1 50 0 1
#> 85 16.44 1 36 0 0
#> 56 12.21 1 60 0 0
#> 90 20.94 1 50 0 1
#> 88 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 92 22.92 1 47 0 1
#> 168 23.72 1 70 0 0
#> 192 16.44 1 31 1 0
#> 117 17.46 1 26 0 1
#> 59 10.16 1 NA 1 0
#> 145.1 10.07 1 65 1 0
#> 110 17.56 1 65 0 1
#> 133.1 14.65 1 57 0 0
#> 5.1 16.43 1 51 0 1
#> 199 19.81 1 NA 0 1
#> 113 22.86 1 34 0 0
#> 63 22.77 1 31 1 0
#> 58 19.34 1 39 0 0
#> 88.1 18.37 1 47 0 0
#> 133.2 14.65 1 57 0 0
#> 117.1 17.46 1 26 0 1
#> 93 10.33 1 52 0 1
#> 181 16.46 1 45 0 1
#> 59.1 10.16 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 91 5.33 1 61 0 1
#> 18.1 15.21 1 49 1 0
#> 107 11.18 1 54 1 0
#> 171 16.57 1 41 0 1
#> 188 16.16 1 46 0 1
#> 127 3.53 1 62 0 1
#> 91.1 5.33 1 61 0 1
#> 136 21.83 1 43 0 1
#> 18.2 15.21 1 49 1 0
#> 5.2 16.43 1 51 0 1
#> 155 13.08 1 26 0 0
#> 106 16.67 1 49 1 0
#> 97 19.14 1 65 0 1
#> 100 16.07 1 60 0 0
#> 43 12.10 1 61 0 1
#> 69 23.23 1 25 0 1
#> 4 17.64 1 NA 0 1
#> 128.1 20.35 1 35 0 1
#> 124 9.73 1 NA 1 0
#> 85.1 16.44 1 36 0 0
#> 56.1 12.21 1 60 0 0
#> 140 12.68 1 59 1 0
#> 180.1 14.82 1 37 0 0
#> 39 15.59 1 37 0 1
#> 56.2 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 8 18.43 1 32 0 0
#> 51 18.23 1 83 0 1
#> 58.1 19.34 1 39 0 0
#> 5.3 16.43 1 51 0 1
#> 49 12.19 1 48 1 0
#> 6.1 15.64 1 39 0 0
#> 194 22.40 1 38 0 1
#> 14 12.89 1 21 0 0
#> 49.1 12.19 1 48 1 0
#> 68 20.62 1 44 0 0
#> 177 12.53 1 75 0 0
#> 81 14.06 1 34 0 0
#> 154.1 12.63 1 20 1 0
#> 134.1 17.81 1 47 1 0
#> 23.1 16.92 1 61 0 0
#> 96 14.54 1 33 0 1
#> 128.2 20.35 1 35 0 1
#> 30 17.43 1 78 0 0
#> 188.1 16.16 1 46 0 1
#> 133.3 14.65 1 57 0 0
#> 63.1 22.77 1 31 1 0
#> 6.2 15.64 1 39 0 0
#> 93.1 10.33 1 52 0 1
#> 175 21.91 1 43 0 0
#> 56.3 12.21 1 60 0 0
#> 108 18.29 1 39 0 1
#> 139 21.49 1 63 1 0
#> 110.1 17.56 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 97.1 19.14 1 65 0 1
#> 6.3 15.64 1 39 0 0
#> 88.2 18.37 1 47 0 0
#> 50 10.02 1 NA 1 0
#> 105.1 19.75 1 60 0 0
#> 159.2 10.55 1 50 0 1
#> 29 15.45 1 68 1 0
#> 41.1 18.02 1 40 1 0
#> 39.1 15.59 1 37 0 1
#> 60.1 13.15 1 38 1 0
#> 96.2 14.54 1 33 0 1
#> 101 9.97 1 10 0 1
#> 52 10.42 1 52 0 1
#> 139.1 21.49 1 63 1 0
#> 39.2 15.59 1 37 0 1
#> 173 24.00 0 19 0 1
#> 73 24.00 0 NA 0 1
#> 176 24.00 0 43 0 1
#> 196 24.00 0 19 0 0
#> 7 24.00 0 37 1 0
#> 198 24.00 0 66 0 1
#> 116 24.00 0 58 0 1
#> 7.1 24.00 0 37 1 0
#> 20 24.00 0 46 1 0
#> 11 24.00 0 42 0 1
#> 62 24.00 0 71 0 0
#> 82 24.00 0 34 0 0
#> 185 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 72 24.00 0 40 0 1
#> 54 24.00 0 53 1 0
#> 119 24.00 0 17 0 0
#> 7.2 24.00 0 37 1 0
#> 47 24.00 0 38 0 1
#> 33 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 95 24.00 0 68 0 1
#> 47.1 24.00 0 38 0 1
#> 20.1 24.00 0 46 1 0
#> 3 24.00 0 31 1 0
#> 198.1 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 7.3 24.00 0 37 1 0
#> 131 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 156 24.00 0 50 1 0
#> 27 24.00 0 63 1 0
#> 141 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 27.1 24.00 0 63 1 0
#> 72.1 24.00 0 40 0 1
#> 109 24.00 0 48 0 0
#> 151 24.00 0 42 0 0
#> 182.1 24.00 0 35 0 0
#> 147 24.00 0 76 1 0
#> 173.1 24.00 0 19 0 1
#> 22 24.00 0 52 1 0
#> 151.1 24.00 0 42 0 0
#> 31 24.00 0 36 0 1
#> 196.1 24.00 0 19 0 0
#> 74 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 152 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 38 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 131.1 24.00 0 66 0 0
#> 11.1 24.00 0 42 0 1
#> 67 24.00 0 25 0 0
#> 27.2 24.00 0 63 1 0
#> 141.1 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 7.4 24.00 0 37 1 0
#> 75 24.00 0 21 1 0
#> 54.1 24.00 0 53 1 0
#> 102 24.00 0 49 0 0
#> 182.2 24.00 0 35 0 0
#> 174.2 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 12 24.00 0 63 0 0
#> 27.3 24.00 0 63 1 0
#> 126 24.00 0 48 0 0
#> 98 24.00 0 34 1 0
#> 54.2 24.00 0 53 1 0
#> 109.1 24.00 0 48 0 0
#> 185.1 24.00 0 44 1 0
#> 182.3 24.00 0 35 0 0
#> 48 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 135.1 24.00 0 58 1 0
#> 115 24.00 0 NA 1 0
#> 47.2 24.00 0 38 0 1
#> 160 24.00 0 31 1 0
#> 75.1 24.00 0 21 1 0
#> 120 24.00 0 68 0 1
#> 21 24.00 0 47 0 0
#> 21.1 24.00 0 47 0 0
#> 115.1 24.00 0 NA 1 0
#> 122 24.00 0 66 0 0
#> 198.2 24.00 0 66 0 1
#> 137 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.181 NA NA NA
#> 2 age, Cure model 0.00984 NA NA NA
#> 3 grade_ii, Cure model -0.651 NA NA NA
#> 4 grade_iii, Cure model 0.401 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00632 NA NA NA
#> 2 grade_ii, Survival model 0.242 NA NA NA
#> 3 grade_iii, Survival model 0.125 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.181030 0.009838 -0.651155 0.400757
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.1
#> Residual Deviance: 251 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.181030463 0.009838417 -0.651155188 0.400757375
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.006322386 0.242431082 0.125409850
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.46320191 0.52643866 0.84796571 0.24711355 0.64993864 0.81274128
#> [7] 0.96171742 0.59428455 0.74823044 0.79841657 0.31869632 0.44413986
#> [13] 0.73346337 0.92253177 0.92253177 0.56951528 0.86874313 0.26000731
#> [19] 0.39414244 0.71130769 0.08424328 0.03133182 0.56951528 0.49974454
#> [25] 0.96171742 0.48171905 0.74823044 0.59428455 0.10568374 0.12614587
#> [31] 0.34089433 0.39414244 0.74823044 0.49974454 0.94873484 0.56100332
#> [37] 0.28492191 0.98096431 0.71130769 0.91585950 0.55242541 0.62608787
#> [43] 0.99365952 0.98096431 0.20638060 0.71130769 0.59428455 0.82683447
#> [49] 0.54378457 0.36269599 0.64198564 0.90914846 0.05956210 0.28492191
#> [55] 0.56951528 0.86874313 0.84095814 0.73346337 0.68075771 0.86874313
#> [61] 0.15853792 0.38360614 0.43422873 0.34089433 0.59428455 0.89571000
#> [67] 0.64993864 0.17505843 0.83390055 0.89571000 0.27255585 0.86182120
#> [73] 0.80558656 0.84796571 0.46320191 0.52643866 0.77698574 0.28492191
#> [79] 0.51755418 0.62608787 0.74823044 0.12614587 0.64993864 0.94873484
#> [85] 0.19091968 0.86874313 0.42410600 0.22129721 0.48171905 0.77698574
#> [91] 0.36269599 0.64993864 0.39414244 0.31869632 0.92253177 0.70366718
#> [97] 0.44413986 0.68075771 0.81274128 0.77698574 0.97454039 0.94216937
#> [103] 0.22129721 0.68075771 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 134 23 154 36 6 60 145 5 133 13 105 41 180
#> 17.81 16.92 12.63 21.19 15.64 13.15 10.07 16.43 14.65 14.34 19.75 18.02 14.82
#> 159 159.1 85 56 90 88 18 92 168 192 117 145.1 110
#> 10.55 10.55 16.44 12.21 20.94 18.37 15.21 22.92 23.72 16.44 17.46 10.07 17.56
#> 133.1 5.1 113 63 58 88.1 133.2 117.1 93 181 128 91 18.1
#> 14.65 16.43 22.86 22.77 19.34 18.37 14.65 17.46 10.33 16.46 20.35 5.33 15.21
#> 107 171 188 127 91.1 136 18.2 5.2 155 106 97 100 43
#> 11.18 16.57 16.16 3.53 5.33 21.83 15.21 16.43 13.08 16.67 19.14 16.07 12.10
#> 69 128.1 85.1 56.1 140 180.1 39 56.2 169 8 51 58.1 5.3
#> 23.23 20.35 16.44 12.21 12.68 14.82 15.59 12.21 22.41 18.43 18.23 19.34 16.43
#> 49 6.1 194 14 49.1 68 177 81 154.1 134.1 23.1 96 128.2
#> 12.19 15.64 22.40 12.89 12.19 20.62 12.53 14.06 12.63 17.81 16.92 14.54 20.35
#> 30 188.1 133.3 63.1 6.2 93.1 175 56.3 108 139 110.1 96.1 97.1
#> 17.43 16.16 14.65 22.77 15.64 10.33 21.91 12.21 18.29 21.49 17.56 14.54 19.14
#> 6.3 88.2 105.1 159.2 29 41.1 39.1 60.1 96.2 101 52 139.1 39.2
#> 15.64 18.37 19.75 10.55 15.45 18.02 15.59 13.15 14.54 9.97 10.42 21.49 15.59
#> 173 176 196 7 198 116 7.1 20 11 62 82 185 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72 54 119 7.2 47 33 165 95 47.1 20.1 3 198.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 7.3 131 182 156 27 141 80 27.1 72.1 109 151 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 173.1 22 151.1 31 196.1 74 144 152 44 142 38 174
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131.1 11.1 67 27.2 141.1 174.1 7.4 75 54.1 102 182.2 174.2 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 27.3 126 98 54.2 109.1 185.1 182.3 48 191 135.1 47.2 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75.1 120 21 21.1 122 198.2 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[77]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.004820825 0.771351157 0.710949414
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.27853265 0.01952656 0.42134105
#> grade_iii, Cure model
#> 1.02613756
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 88 18.37 1 47 0 0
#> 169 22.41 1 46 0 0
#> 85 16.44 1 36 0 0
#> 125 15.65 1 67 1 0
#> 199 19.81 1 NA 0 1
#> 187 9.92 1 39 1 0
#> 195 11.76 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 32 20.90 1 37 1 0
#> 100 16.07 1 60 0 0
#> 195.1 11.76 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 113 22.86 1 34 0 0
#> 170 19.54 1 43 0 1
#> 175 21.91 1 43 0 0
#> 45 17.42 1 54 0 1
#> 79 16.23 1 54 1 0
#> 15 22.68 1 48 0 0
#> 149 8.37 1 33 1 0
#> 158 20.14 1 74 1 0
#> 123 13.00 1 44 1 0
#> 133 14.65 1 57 0 0
#> 167 15.55 1 56 1 0
#> 130 16.47 1 53 0 1
#> 169.1 22.41 1 46 0 0
#> 88.1 18.37 1 47 0 0
#> 6 15.64 1 39 0 0
#> 77.1 7.27 1 67 0 1
#> 16 8.71 1 71 0 1
#> 114 13.68 1 NA 0 0
#> 79.1 16.23 1 54 1 0
#> 153 21.33 1 55 1 0
#> 171 16.57 1 41 0 1
#> 181 16.46 1 45 0 1
#> 92 22.92 1 47 0 1
#> 10 10.53 1 34 0 0
#> 177 12.53 1 75 0 0
#> 18 15.21 1 49 1 0
#> 154 12.63 1 20 1 0
#> 164 23.60 1 76 0 1
#> 139 21.49 1 63 1 0
#> 134 17.81 1 47 1 0
#> 181.1 16.46 1 45 0 1
#> 45.1 17.42 1 54 0 1
#> 36 21.19 1 48 0 1
#> 167.1 15.55 1 56 1 0
#> 91 5.33 1 61 0 1
#> 195.2 11.76 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 66 22.13 1 53 0 0
#> 127 3.53 1 62 0 1
#> 175.1 21.91 1 43 0 0
#> 177.1 12.53 1 75 0 0
#> 127.1 3.53 1 62 0 1
#> 114.1 13.68 1 NA 0 0
#> 114.2 13.68 1 NA 0 0
#> 110 17.56 1 65 0 1
#> 29 15.45 1 68 1 0
#> 133.1 14.65 1 57 0 0
#> 113.1 22.86 1 34 0 0
#> 41 18.02 1 40 1 0
#> 81 14.06 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 181.2 16.46 1 45 0 1
#> 199.1 19.81 1 NA 0 1
#> 140 12.68 1 59 1 0
#> 52 10.42 1 52 0 1
#> 13 14.34 1 54 0 1
#> 113.2 22.86 1 34 0 0
#> 39 15.59 1 37 0 1
#> 136 21.83 1 43 0 1
#> 99 21.19 1 38 0 1
#> 150 20.33 1 48 0 0
#> 91.1 5.33 1 61 0 1
#> 134.1 17.81 1 47 1 0
#> 13.1 14.34 1 54 0 1
#> 171.1 16.57 1 41 0 1
#> 37 12.52 1 57 1 0
#> 145 10.07 1 65 1 0
#> 183 9.24 1 67 1 0
#> 127.2 3.53 1 62 0 1
#> 139.1 21.49 1 63 1 0
#> 42 12.43 1 49 0 1
#> 32.1 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 188 16.16 1 46 0 1
#> 78 23.88 1 43 0 0
#> 181.3 16.46 1 45 0 1
#> 41.1 18.02 1 40 1 0
#> 97 19.14 1 65 0 1
#> 78.1 23.88 1 43 0 0
#> 37.1 12.52 1 57 1 0
#> 197 21.60 1 69 1 0
#> 127.3 3.53 1 62 0 1
#> 40 18.00 1 28 1 0
#> 55.1 19.34 1 69 0 1
#> 52.1 10.42 1 52 0 1
#> 139.2 21.49 1 63 1 0
#> 145.1 10.07 1 65 1 0
#> 106 16.67 1 49 1 0
#> 133.2 14.65 1 57 0 0
#> 190 20.81 1 42 1 0
#> 49 12.19 1 48 1 0
#> 130.1 16.47 1 53 0 1
#> 4 17.64 1 NA 0 1
#> 76 19.22 1 54 0 1
#> 40.1 18.00 1 28 1 0
#> 25 6.32 1 34 1 0
#> 5 16.43 1 51 0 1
#> 4.1 17.64 1 NA 0 1
#> 100.1 16.07 1 60 0 0
#> 182 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 200 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 28 24.00 0 67 1 0
#> 20 24.00 0 46 1 0
#> 172 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 9 24.00 0 31 1 0
#> 54 24.00 0 53 1 0
#> 87 24.00 0 27 0 0
#> 144 24.00 0 28 0 1
#> 141 24.00 0 44 1 0
#> 64 24.00 0 43 0 0
#> 146 24.00 0 63 1 0
#> 33 24.00 0 53 0 0
#> 28.1 24.00 0 67 1 0
#> 64.1 24.00 0 43 0 0
#> 80 24.00 0 41 0 0
#> 53 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 31 24.00 0 36 0 1
#> 151 24.00 0 42 0 0
#> 38 24.00 0 31 1 0
#> 132 24.00 0 55 0 0
#> 104 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 20.1 24.00 0 46 1 0
#> 35 24.00 0 51 0 0
#> 191 24.00 0 60 0 1
#> 172.1 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 9.1 24.00 0 31 1 0
#> 144.1 24.00 0 28 0 1
#> 11 24.00 0 42 0 1
#> 162 24.00 0 51 0 0
#> 65 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 19 24.00 0 57 0 1
#> 22.1 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 156 24.00 0 50 1 0
#> 172.2 24.00 0 41 0 0
#> 62.1 24.00 0 71 0 0
#> 34 24.00 0 36 0 0
#> 62.2 24.00 0 71 0 0
#> 3 24.00 0 31 1 0
#> 35.1 24.00 0 51 0 0
#> 46 24.00 0 71 0 0
#> 22.2 24.00 0 52 1 0
#> 53.1 24.00 0 32 0 1
#> 35.2 24.00 0 51 0 0
#> 103 24.00 0 56 1 0
#> 144.2 24.00 0 28 0 1
#> 191.1 24.00 0 60 0 1
#> 19.1 24.00 0 57 0 1
#> 80.1 24.00 0 41 0 0
#> 116 24.00 0 58 0 1
#> 196.1 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 38.1 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 103.1 24.00 0 56 1 0
#> 98 24.00 0 34 1 0
#> 65.1 24.00 0 57 1 0
#> 156.1 24.00 0 50 1 0
#> 33.1 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 122 24.00 0 66 0 0
#> 20.2 24.00 0 46 1 0
#> 71 24.00 0 51 0 0
#> 191.2 24.00 0 60 0 1
#> 126 24.00 0 48 0 0
#> 35.3 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 161 24.00 0 45 0 0
#> 146.1 24.00 0 63 1 0
#> 87.1 24.00 0 27 0 0
#> 148 24.00 0 61 1 0
#> 162.1 24.00 0 51 0 0
#> 121 24.00 0 57 1 0
#> 178.1 24.00 0 52 1 0
#> 71.1 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 72 24.00 0 40 0 1
#> 103.2 24.00 0 56 1 0
#> 12 24.00 0 63 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.28 NA NA NA
#> 2 age, Cure model 0.0195 NA NA NA
#> 3 grade_ii, Cure model 0.421 NA NA NA
#> 4 grade_iii, Cure model 1.03 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00482 NA NA NA
#> 2 grade_ii, Survival model 0.771 NA NA NA
#> 3 grade_iii, Survival model 0.711 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.27853 0.01953 0.42134 1.02614
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 259.6
#> Residual Deviance: 248.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.27853265 0.01952656 0.42134105 1.02613756
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.004820825 0.771351157 0.710949414
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.59633464 0.28624740 0.75573322 0.79733308 0.94268920 0.96109675
#> [7] 0.49647196 0.78570601 0.55988843 0.20381259 0.54994562 0.34673214
#> [13] 0.68388483 0.76802034 0.26464774 0.95655195 0.53972474 0.87356482
#> [19] 0.84183563 0.81451196 0.71825484 0.28624740 0.59633464 0.80308433
#> [25] 0.96109675 0.95197375 0.76802034 0.46000007 0.70484972 0.73126454
#> [31] 0.17972601 0.91885918 0.88900723 0.83102966 0.88390610 0.14933072
#> [37] 0.42037714 0.65415597 0.73126454 0.68388483 0.47291148 0.81451196
#> [43] 0.97444890 0.67658428 0.32638228 0.98316455 0.34673214 0.88900723
#> [49] 0.98316455 0.66917923 0.82556036 0.84183563 0.20381259 0.62229318
#> [55] 0.86831336 0.83643708 0.73126454 0.87876397 0.92373834 0.85783094
#> [61] 0.20381259 0.80882708 0.38523278 0.47291148 0.52908273 0.97444890
#> [67] 0.65415597 0.85783094 0.70484972 0.89912977 0.93330796 0.94735408
#> [73] 0.98316455 0.42037714 0.90904616 0.49647196 0.61376418 0.77984159
#> [79] 0.06624659 0.73126454 0.62229318 0.58748902 0.06624659 0.89912977
#> [85] 0.40357460 0.98316455 0.63851765 0.55988843 0.92373834 0.42037714
#> [91] 0.93330796 0.69791886 0.84183563 0.51838470 0.91397539 0.71825484
#> [97] 0.57839910 0.63851765 0.97001241 0.76191649 0.78570601 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000
#>
#> $Time
#> 88 169 85 125 187 77 32 100 55 113 170 175 45
#> 18.37 22.41 16.44 15.65 9.92 7.27 20.90 16.07 19.34 22.86 19.54 21.91 17.42
#> 79 15 149 158 123 133 167 130 169.1 88.1 6 77.1 16
#> 16.23 22.68 8.37 20.14 13.00 14.65 15.55 16.47 22.41 18.37 15.64 7.27 8.71
#> 79.1 153 171 181 92 10 177 18 154 164 139 134 181.1
#> 16.23 21.33 16.57 16.46 22.92 10.53 12.53 15.21 12.63 23.60 21.49 17.81 16.46
#> 45.1 36 167.1 91 117 66 127 175.1 177.1 127.1 110 29 133.1
#> 17.42 21.19 15.55 5.33 17.46 22.13 3.53 21.91 12.53 3.53 17.56 15.45 14.65
#> 113.1 41 81 157 181.2 140 52 13 113.2 39 136 99 150
#> 22.86 18.02 14.06 15.10 16.46 12.68 10.42 14.34 22.86 15.59 21.83 21.19 20.33
#> 91.1 134.1 13.1 171.1 37 145 183 127.2 139.1 42 32.1 51 188
#> 5.33 17.81 14.34 16.57 12.52 10.07 9.24 3.53 21.49 12.43 20.90 18.23 16.16
#> 78 181.3 41.1 97 78.1 37.1 197 127.3 40 55.1 52.1 139.2 145.1
#> 23.88 16.46 18.02 19.14 23.88 12.52 21.60 3.53 18.00 19.34 10.42 21.49 10.07
#> 106 133.2 190 49 130.1 76 40.1 25 5 100.1 182 82 200
#> 16.67 14.65 20.81 12.19 16.47 19.22 18.00 6.32 16.43 16.07 24.00 24.00 24.00
#> 196 28 20 172 62 9 54 87 144 141 64 146 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 64.1 80 53 119 31 151 38 132 104 84 20.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191 172.1 178 9.1 144.1 11 162 65 22 95 19 22.1 95.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156 172.2 62.1 34 62.2 3 35.1 46 22.2 53.1 35.2 103 144.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 19.1 80.1 116 196.1 176 38.1 64.2 103.1 98 65.1 156.1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 20.2 71 191.2 126 35.3 138 161 146.1 87.1 148 162.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 178.1 71.1 17 72 103.2 12
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[78]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.0001833177 0.5219377063 0.2969726711
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.89071460 0.01346406 0.42733228
#> grade_iii, Cure model
#> 1.00615034
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 157 15.10 1 47 0 0
#> 157.1 15.10 1 47 0 0
#> 177 12.53 1 75 0 0
#> 149 8.37 1 33 1 0
#> 18 15.21 1 49 1 0
#> 105 19.75 1 60 0 0
#> 55 19.34 1 69 0 1
#> 194 22.40 1 38 0 1
#> 134 17.81 1 47 1 0
#> 61 10.12 1 36 0 1
#> 41 18.02 1 40 1 0
#> 181 16.46 1 45 0 1
#> 188 16.16 1 46 0 1
#> 128 20.35 1 35 0 1
#> 90 20.94 1 50 0 1
#> 10 10.53 1 34 0 0
#> 50 10.02 1 NA 1 0
#> 70 7.38 1 30 1 0
#> 89 11.44 1 NA 0 0
#> 70.1 7.38 1 30 1 0
#> 179 18.63 1 42 0 0
#> 190 20.81 1 42 1 0
#> 129 23.41 1 53 1 0
#> 159 10.55 1 50 0 1
#> 49 12.19 1 48 1 0
#> 78 23.88 1 43 0 0
#> 158 20.14 1 74 1 0
#> 107 11.18 1 54 1 0
#> 24 23.89 1 38 0 0
#> 86 23.81 1 58 0 1
#> 49.1 12.19 1 48 1 0
#> 150 20.33 1 48 0 0
#> 36 21.19 1 48 0 1
#> 168 23.72 1 70 0 0
#> 86.1 23.81 1 58 0 1
#> 60 13.15 1 38 1 0
#> 113 22.86 1 34 0 0
#> 13 14.34 1 54 0 1
#> 59 10.16 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 93 10.33 1 52 0 1
#> 105.1 19.75 1 60 0 0
#> 14 12.89 1 21 0 0
#> 134.1 17.81 1 47 1 0
#> 190.1 20.81 1 42 1 0
#> 117 17.46 1 26 0 1
#> 166 19.98 1 48 0 0
#> 155 13.08 1 26 0 0
#> 136 21.83 1 43 0 1
#> 96 14.54 1 33 0 1
#> 60.1 13.15 1 38 1 0
#> 194.1 22.40 1 38 0 1
#> 13.1 14.34 1 54 0 1
#> 127 3.53 1 62 0 1
#> 113.1 22.86 1 34 0 0
#> 128.1 20.35 1 35 0 1
#> 108 18.29 1 39 0 1
#> 8 18.43 1 32 0 0
#> 153 21.33 1 55 1 0
#> 69 23.23 1 25 0 1
#> 99 21.19 1 38 0 1
#> 157.2 15.10 1 47 0 0
#> 37 12.52 1 57 1 0
#> 30 17.43 1 78 0 0
#> 57 14.46 1 45 0 1
#> 41.1 18.02 1 40 1 0
#> 194.2 22.40 1 38 0 1
#> 16 8.71 1 71 0 1
#> 42 12.43 1 49 0 1
#> 25 6.32 1 34 1 0
#> 41.2 18.02 1 40 1 0
#> 166.1 19.98 1 48 0 0
#> 149.1 8.37 1 33 1 0
#> 197 21.60 1 69 1 0
#> 97 19.14 1 65 0 1
#> 96.1 14.54 1 33 0 1
#> 124 9.73 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 16.1 8.71 1 71 0 1
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 58 19.34 1 39 0 0
#> 124.1 9.73 1 NA 1 0
#> 89.1 11.44 1 NA 0 0
#> 77 7.27 1 67 0 1
#> 79 16.23 1 54 1 0
#> 107.1 11.18 1 54 1 0
#> 81 14.06 1 34 0 0
#> 55.1 19.34 1 69 0 1
#> 57.1 14.46 1 45 0 1
#> 197.1 21.60 1 69 1 0
#> 170 19.54 1 43 0 1
#> 170.1 19.54 1 43 0 1
#> 164 23.60 1 76 0 1
#> 166.2 19.98 1 48 0 0
#> 140 12.68 1 59 1 0
#> 52 10.42 1 52 0 1
#> 190.2 20.81 1 42 1 0
#> 8.1 18.43 1 32 0 0
#> 57.2 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 194.3 22.40 1 38 0 1
#> 63.1 22.77 1 31 1 0
#> 6 15.64 1 39 0 0
#> 124.2 9.73 1 NA 1 0
#> 197.2 21.60 1 69 1 0
#> 15 22.68 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 68 20.62 1 44 0 0
#> 52.1 10.42 1 52 0 1
#> 125 15.65 1 67 1 0
#> 47 24.00 0 38 0 1
#> 65 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 182 24.00 0 35 0 0
#> 74 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 152 24.00 0 36 0 1
#> 163 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 12 24.00 0 63 0 0
#> 11 24.00 0 42 0 1
#> 103 24.00 0 56 1 0
#> 160 24.00 0 31 1 0
#> 64 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 72 24.00 0 40 0 1
#> 148 24.00 0 61 1 0
#> 160.1 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 109 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 109.1 24.00 0 48 0 0
#> 19 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 131 24.00 0 66 0 0
#> 161.1 24.00 0 45 0 0
#> 2 24.00 0 9 0 0
#> 27 24.00 0 63 1 0
#> 151 24.00 0 42 0 0
#> 148.1 24.00 0 61 1 0
#> 72.1 24.00 0 40 0 1
#> 104 24.00 0 50 1 0
#> 185 24.00 0 44 1 0
#> 119 24.00 0 17 0 0
#> 160.2 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 182.1 24.00 0 35 0 0
#> 75 24.00 0 21 1 0
#> 176 24.00 0 43 0 1
#> 98 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 67.1 24.00 0 25 0 0
#> 185.1 24.00 0 44 1 0
#> 152.1 24.00 0 36 0 1
#> 46.1 24.00 0 71 0 0
#> 112 24.00 0 61 0 0
#> 65.1 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 22 24.00 0 52 1 0
#> 53 24.00 0 32 0 1
#> 22.1 24.00 0 52 1 0
#> 84 24.00 0 39 0 1
#> 95 24.00 0 68 0 1
#> 196 24.00 0 19 0 0
#> 109.2 24.00 0 48 0 0
#> 71 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 1 24.00 0 23 1 0
#> 137 24.00 0 45 1 0
#> 173.1 24.00 0 19 0 1
#> 193 24.00 0 45 0 1
#> 71.1 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 82 24.00 0 34 0 0
#> 84.1 24.00 0 39 0 1
#> 54 24.00 0 53 1 0
#> 20 24.00 0 46 1 0
#> 118.1 24.00 0 44 1 0
#> 95.1 24.00 0 68 0 1
#> 67.2 24.00 0 25 0 0
#> 20.1 24.00 0 46 1 0
#> 73 24.00 0 NA 0 1
#> 73.1 24.00 0 NA 0 1
#> 161.2 24.00 0 45 0 0
#> 122 24.00 0 66 0 0
#> 132 24.00 0 55 0 0
#> 3 24.00 0 31 1 0
#> 182.2 24.00 0 35 0 0
#> 104.1 24.00 0 50 1 0
#> 191 24.00 0 60 0 1
#> 11.1 24.00 0 42 0 1
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 196.1 24.00 0 19 0 0
#> 151.1 24.00 0 42 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.891 NA NA NA
#> 2 age, Cure model 0.0135 NA NA NA
#> 3 grade_ii, Cure model 0.427 NA NA NA
#> 4 grade_iii, Cure model 1.01 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.000183 NA NA NA
#> 2 grade_ii, Survival model 0.522 NA NA NA
#> 3 grade_iii, Survival model 0.297 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89071 0.01346 0.42733 1.00615
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 253.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.89071460 0.01346406 0.42733228 1.00615034
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.0001833177 0.5219377063 0.2969726711
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.68546731 0.68546731 0.81075389 0.93667652 0.67741142 0.45161392
#> [7] 0.48828374 0.22008796 0.58561439 0.90040161 0.55994235 0.61947179
#> [13] 0.63627012 0.38672468 0.33872386 0.87093484 0.95091353 0.95091353
#> [19] 0.52405051 0.34894188 0.12380086 0.86351674 0.83371232 0.03529057
#> [25] 0.41490235 0.84870201 0.01289224 0.05840152 0.83371232 0.40543483
#> [31] 0.31839475 0.08980197 0.05840152 0.77217546 0.15367099 0.74871541
#> [37] 0.18164484 0.89304536 0.45161392 0.79532113 0.58561439 0.34894188
#> [43] 0.60252273 0.42422887 0.78758031 0.26475564 0.70935931 0.77217546
#> [49] 0.22008796 0.74871541 0.99302788 0.15367099 0.38672468 0.55096968
#> [55] 0.53307328 0.30783303 0.13900728 0.31839475 0.68546731 0.81844653
#> [61] 0.61099642 0.72525688 0.55994235 0.22008796 0.92229191 0.82609120
#> [67] 0.97903478 0.55994235 0.42422887 0.93667652 0.27652978 0.51502894
#> [73] 0.70935931 0.98603954 0.92229191 0.91503402 0.90773767 0.66929080
#> [79] 0.48828374 0.96500789 0.62790852 0.84870201 0.76432826 0.48828374
#> [85] 0.72525688 0.27652978 0.47006863 0.47006863 0.10723814 0.42422887
#> [91] 0.80306224 0.87835333 0.34894188 0.53307328 0.72525688 0.66110419
#> [97] 0.22008796 0.18164484 0.65284929 0.27652978 0.20699273 0.96500789
#> [103] 0.37709469 0.87835333 0.64459514 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 157 157.1 177 149 18 105 55 194 134 61 41 181 188
#> 15.10 15.10 12.53 8.37 15.21 19.75 19.34 22.40 17.81 10.12 18.02 16.46 16.16
#> 128 90 10 70 70.1 179 190 129 159 49 78 158 107
#> 20.35 20.94 10.53 7.38 7.38 18.63 20.81 23.41 10.55 12.19 23.88 20.14 11.18
#> 24 86 49.1 150 36 168 86.1 60 113 13 63 93 105.1
#> 23.89 23.81 12.19 20.33 21.19 23.72 23.81 13.15 22.86 14.34 22.77 10.33 19.75
#> 14 134.1 190.1 117 166 155 136 96 60.1 194.1 13.1 127 113.1
#> 12.89 17.81 20.81 17.46 19.98 13.08 21.83 14.54 13.15 22.40 14.34 3.53 22.86
#> 128.1 108 8 153 69 99 157.2 37 30 57 41.1 194.2 16
#> 20.35 18.29 18.43 21.33 23.23 21.19 15.10 12.52 17.43 14.46 18.02 22.40 8.71
#> 42 25 41.2 166.1 149.1 197 97 96.1 91 16.1 183 187 29
#> 12.43 6.32 18.02 19.98 8.37 21.60 19.14 14.54 5.33 8.71 9.24 9.92 15.45
#> 58 77 79 107.1 81 55.1 57.1 197.1 170 170.1 164 166.2 140
#> 19.34 7.27 16.23 11.18 14.06 19.34 14.46 21.60 19.54 19.54 23.60 19.98 12.68
#> 52 190.2 8.1 57.2 167 194.3 63.1 6 197.2 15 77.1 68 52.1
#> 10.42 20.81 18.43 14.46 15.55 22.40 22.77 15.64 21.60 22.68 7.27 20.62 10.42
#> 125 47 65 83 138 182 74 67 152 163 172 12 11
#> 15.65 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103 160 64 173 147 72 148 160.1 46 44 109 121 109.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 161 131 161.1 2 27 151 148.1 72.1 104 185 119 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62 182.1 75 176 98 118 67.1 185.1 152.1 46.1 112 65.1 135
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22 53 22.1 84 95 196 109.2 71 146 1 137 173.1 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71.1 176.1 82 84.1 54 20 118.1 95.1 67.2 20.1 161.2 122 132
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3 182.2 104.1 191 11.1 21 200 196.1 151.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[79]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01678303 0.67116796 0.42937718
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.84283121 0.01091593 0.63919646
#> grade_iii, Cure model
#> 1.00481079
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 114 13.68 1 NA 0 0
#> 192 16.44 1 31 1 0
#> 159 10.55 1 50 0 1
#> 70 7.38 1 30 1 0
#> 140 12.68 1 59 1 0
#> 170 19.54 1 43 0 1
#> 55 19.34 1 69 0 1
#> 43 12.10 1 61 0 1
#> 101 9.97 1 10 0 1
#> 184 17.77 1 38 0 0
#> 58 19.34 1 39 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 167 15.55 1 56 1 0
#> 134 17.81 1 47 1 0
#> 97 19.14 1 65 0 1
#> 24 23.89 1 38 0 0
#> 123 13.00 1 44 1 0
#> 169 22.41 1 46 0 0
#> 18 15.21 1 49 1 0
#> 30 17.43 1 78 0 0
#> 159.1 10.55 1 50 0 1
#> 66 22.13 1 53 0 0
#> 58.1 19.34 1 39 0 0
#> 139 21.49 1 63 1 0
#> 197 21.60 1 69 1 0
#> 61 10.12 1 36 0 1
#> 13 14.34 1 54 0 1
#> 149 8.37 1 33 1 0
#> 192.1 16.44 1 31 1 0
#> 99 21.19 1 38 0 1
#> 192.2 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 164 23.60 1 76 0 1
#> 59 10.16 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 8 18.43 1 32 0 0
#> 105 19.75 1 60 0 0
#> 170.1 19.54 1 43 0 1
#> 77 7.27 1 67 0 1
#> 61.1 10.12 1 36 0 1
#> 92 22.92 1 47 0 1
#> 92.1 22.92 1 47 0 1
#> 192.3 16.44 1 31 1 0
#> 101.1 9.97 1 10 0 1
#> 189 10.51 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 145 10.07 1 65 1 0
#> 49 12.19 1 48 1 0
#> 125 15.65 1 67 1 0
#> 153.1 21.33 1 55 1 0
#> 57 14.46 1 45 0 1
#> 114.1 13.68 1 NA 0 0
#> 154 12.63 1 20 1 0
#> 113 22.86 1 34 0 0
#> 192.4 16.44 1 31 1 0
#> 51 18.23 1 83 0 1
#> 139.1 21.49 1 63 1 0
#> 133 14.65 1 57 0 0
#> 150.1 20.33 1 48 0 0
#> 61.2 10.12 1 36 0 1
#> 32 20.90 1 37 1 0
#> 66.1 22.13 1 53 0 0
#> 99.1 21.19 1 38 0 1
#> 4 17.64 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 58.2 19.34 1 39 0 0
#> 10 10.53 1 34 0 0
#> 189.1 10.51 1 NA 1 0
#> 91 5.33 1 61 0 1
#> 4.1 17.64 1 NA 0 1
#> 168 23.72 1 70 0 0
#> 13.1 14.34 1 54 0 1
#> 85 16.44 1 36 0 0
#> 85.1 16.44 1 36 0 0
#> 37 12.52 1 57 1 0
#> 57.1 14.46 1 45 0 1
#> 189.2 10.51 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 168.1 23.72 1 70 0 0
#> 128 20.35 1 35 0 1
#> 69 23.23 1 25 0 1
#> 13.2 14.34 1 54 0 1
#> 187 9.92 1 39 1 0
#> 42 12.43 1 49 0 1
#> 134.1 17.81 1 47 1 0
#> 14 12.89 1 21 0 0
#> 86 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 133.1 14.65 1 57 0 0
#> 129 23.41 1 53 1 0
#> 77.1 7.27 1 67 0 1
#> 92.2 22.92 1 47 0 1
#> 61.3 10.12 1 36 0 1
#> 154.1 12.63 1 20 1 0
#> 190 20.81 1 42 1 0
#> 159.2 10.55 1 50 0 1
#> 106 16.67 1 49 1 0
#> 96 14.54 1 33 0 1
#> 134.2 17.81 1 47 1 0
#> 99.2 21.19 1 38 0 1
#> 37.1 12.52 1 57 1 0
#> 167.1 15.55 1 56 1 0
#> 77.2 7.27 1 67 0 1
#> 184.1 17.77 1 38 0 0
#> 26.1 15.77 1 49 0 1
#> 124 9.73 1 NA 1 0
#> 8.1 18.43 1 32 0 0
#> 25 6.32 1 34 1 0
#> 110 17.56 1 65 0 1
#> 8.2 18.43 1 32 0 0
#> 62 24.00 0 71 0 0
#> 73 24.00 0 NA 0 1
#> 12 24.00 0 63 0 0
#> 141 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 22 24.00 0 52 1 0
#> 115 24.00 0 NA 1 0
#> 11 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#> 196 24.00 0 19 0 0
#> 160 24.00 0 31 1 0
#> 11.1 24.00 0 42 0 1
#> 19 24.00 0 57 0 1
#> 38 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 75 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 7 24.00 0 37 1 0
#> 11.2 24.00 0 42 0 1
#> 156 24.00 0 50 1 0
#> 46 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 72 24.00 0 40 0 1
#> 19.1 24.00 0 57 0 1
#> 156.1 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 73.1 24.00 0 NA 0 1
#> 44 24.00 0 56 0 0
#> 34 24.00 0 36 0 0
#> 186 24.00 0 45 1 0
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 35 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 47.1 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 83 24.00 0 6 0 0
#> 7.1 24.00 0 37 1 0
#> 165 24.00 0 47 0 0
#> 178 24.00 0 52 1 0
#> 12.1 24.00 0 63 0 0
#> 65.1 24.00 0 57 1 0
#> 28 24.00 0 67 1 0
#> 94 24.00 0 51 0 1
#> 151 24.00 0 42 0 0
#> 160.1 24.00 0 31 1 0
#> 102 24.00 0 49 0 0
#> 12.2 24.00 0 63 0 0
#> 143 24.00 0 51 0 0
#> 152 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 98 24.00 0 34 1 0
#> 174 24.00 0 49 1 0
#> 160.2 24.00 0 31 1 0
#> 17 24.00 0 38 0 1
#> 118 24.00 0 44 1 0
#> 152.1 24.00 0 36 0 1
#> 165.1 24.00 0 47 0 0
#> 119 24.00 0 17 0 0
#> 67.2 24.00 0 25 0 0
#> 12.3 24.00 0 63 0 0
#> 193.1 24.00 0 45 0 1
#> 109 24.00 0 48 0 0
#> 186.1 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 9 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 119.1 24.00 0 17 0 0
#> 120 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 102.1 24.00 0 49 0 0
#> 109.1 24.00 0 48 0 0
#> 132.1 24.00 0 55 0 0
#> 116 24.00 0 58 0 1
#> 109.2 24.00 0 48 0 0
#> 152.2 24.00 0 36 0 1
#> 151.1 24.00 0 42 0 0
#> 21 24.00 0 47 0 0
#> 119.2 24.00 0 17 0 0
#> 12.4 24.00 0 63 0 0
#> 64 24.00 0 43 0 0
#> 120.1 24.00 0 68 0 1
#> 9.1 24.00 0 31 1 0
#> 47.2 24.00 0 38 0 1
#> 163.1 24.00 0 66 0 0
#> 20 24.00 0 46 1 0
#> 31 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.843 NA NA NA
#> 2 age, Cure model 0.0109 NA NA NA
#> 3 grade_ii, Cure model 0.639 NA NA NA
#> 4 grade_iii, Cure model 1.00 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0168 NA NA NA
#> 2 grade_ii, Survival model 0.671 NA NA NA
#> 3 grade_iii, Survival model 0.429 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84283 0.01092 0.63920 1.00481
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.9
#> Residual Deviance: 249.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.84283121 0.01091593 0.63919646 1.00481079
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01678303 0.67116796 0.42937718
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.1393934584 0.3660693497 0.7519001098 0.9205918231 0.6514523149
#> [6] 0.1630030355 0.1793627747 0.7391193525 0.8682088395 0.3115104613
#> [11] 0.1793627747 0.0758363429 0.2135091180 0.4832293618 0.2812389896
#> [16] 0.2227610520 0.0001190401 0.6263255261 0.0338988666 0.5061375862
#> [21] 0.3436274654 0.7519001098 0.0390330031 0.1793627747 0.0628332646
#> [26] 0.0564103700 0.8033270557 0.5773600950 0.9074670976 0.3660693497
#> [31] 0.0893604078 0.3660693497 0.2607848917 0.0061970422 0.0502579345
#> [36] 0.2322027870 0.1548212174 0.1630030355 0.9336824818 0.8033270557
#> [41] 0.0177746426 0.0177746426 0.3660693497 0.8682088395 0.4493138738
#> [46] 0.8549340334 0.7264368682 0.4717658775 0.0758363429 0.5533746149
#> [51] 0.6641193316 0.0291520447 0.3660693497 0.2708925479 0.0628332646
#> [56] 0.5177616739 0.1393934584 0.8033270557 0.1171251302 0.0390330031
#> [61] 0.0893604078 0.6138151170 0.1793627747 0.7902408148 0.9865734055
#> [66] 0.0019459436 0.5773600950 0.3660693497 0.3660693497 0.6888395739
#> [71] 0.5533746149 0.1097086904 0.0019459436 0.1319248521 0.0138162610
#> [76] 0.5773600950 0.8943187025 0.7137821764 0.2812389896 0.6388522248
#> [81] 0.0007897283 0.4381280897 0.5177616739 0.0098547951 0.9336824818
#> [86] 0.0177746426 0.8033270557 0.6641193316 0.1245176379 0.7519001098
#> [91] 0.3548234977 0.5413950995 0.2812389896 0.0893604078 0.6888395739
#> [96] 0.4832293618 0.9336824818 0.3115104613 0.4493138738 0.2322027870
#> [101] 0.9732281960 0.3326915256 0.2322027870 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 150 192 159 70 140 170 55 43 101 184 58 153 76
#> 20.33 16.44 10.55 7.38 12.68 19.54 19.34 12.10 9.97 17.77 19.34 21.33 19.22
#> 167 134 97 24 123 169 18 30 159.1 66 58.1 139 197
#> 15.55 17.81 19.14 23.89 13.00 22.41 15.21 17.43 10.55 22.13 19.34 21.49 21.60
#> 61 13 149 192.1 99 192.2 88 164 136 8 105 170.1 77
#> 10.12 14.34 8.37 16.44 21.19 16.44 18.37 23.60 21.83 18.43 19.75 19.54 7.27
#> 61.1 92 92.1 192.3 101.1 26 145 49 125 153.1 57 154 113
#> 10.12 22.92 22.92 16.44 9.97 15.77 10.07 12.19 15.65 21.33 14.46 12.63 22.86
#> 192.4 51 139.1 133 150.1 61.2 32 66.1 99.1 81 58.2 10 91
#> 16.44 18.23 21.49 14.65 20.33 10.12 20.90 22.13 21.19 14.06 19.34 10.53 5.33
#> 168 13.1 85 85.1 37 57.1 90 168.1 128 69 13.2 187 42
#> 23.72 14.34 16.44 16.44 12.52 14.46 20.94 23.72 20.35 23.23 14.34 9.92 12.43
#> 134.1 14 86 188 133.1 129 77.1 92.2 61.3 154.1 190 159.2 106
#> 17.81 12.89 23.81 16.16 14.65 23.41 7.27 22.92 10.12 12.63 20.81 10.55 16.67
#> 96 134.2 99.2 37.1 167.1 77.2 184.1 26.1 8.1 25 110 8.2 62
#> 14.54 17.81 21.19 12.52 15.55 7.27 17.77 15.77 18.43 6.32 17.56 18.43 24.00
#> 12 141 65 22 11 173 196 160 11.1 19 38 67 75
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 132 7 11.2 156 46 163 72 19.1 156.1 131 172 44 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 186 126 47 35 84 47.1 67.1 83 7.1 165 178 12.1 65.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 94 151 160.1 102 12.2 143 152 193 98 174 160.2 17
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 152.1 165.1 119 67.2 12.3 193.1 109 186.1 48 9 185 119.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 71 102.1 109.1 132.1 116 109.2 152.2 151.1 21 119.2 12.4 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120.1 9.1 47.2 163.1 20 31
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[80]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001096246 0.363419540 0.486119277
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.05971072 0.01500402 0.65589390
#> grade_iii, Cure model
#> 1.23008760
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 39 15.59 1 37 0 1
#> 81 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 168 23.72 1 70 0 0
#> 13 14.34 1 54 0 1
#> 170 19.54 1 43 0 1
#> 77 7.27 1 67 0 1
#> 91 5.33 1 61 0 1
#> 8 18.43 1 32 0 0
#> 184 17.77 1 38 0 0
#> 159 10.55 1 50 0 1
#> 145 10.07 1 65 1 0
#> 10 10.53 1 34 0 0
#> 23 16.92 1 61 0 0
#> 133 14.65 1 57 0 0
#> 105 19.75 1 60 0 0
#> 188 16.16 1 46 0 1
#> 177 12.53 1 75 0 0
#> 113 22.86 1 34 0 0
#> 5 16.43 1 51 0 1
#> 192 16.44 1 31 1 0
#> 15 22.68 1 48 0 0
#> 140 12.68 1 59 1 0
#> 159.1 10.55 1 50 0 1
#> 14 12.89 1 21 0 0
#> 155 13.08 1 26 0 0
#> 139 21.49 1 63 1 0
#> 164 23.60 1 76 0 1
#> 167 15.55 1 56 1 0
#> 183 9.24 1 67 1 0
#> 127 3.53 1 62 0 1
#> 181 16.46 1 45 0 1
#> 4 17.64 1 NA 0 1
#> 130 16.47 1 53 0 1
#> 24 23.89 1 38 0 0
#> 57 14.46 1 45 0 1
#> 179 18.63 1 42 0 0
#> 4.1 17.64 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 26 15.77 1 49 0 1
#> 195 11.76 1 NA 1 0
#> 187 9.92 1 39 1 0
#> 170.1 19.54 1 43 0 1
#> 77.1 7.27 1 67 0 1
#> 183.1 9.24 1 67 1 0
#> 25 6.32 1 34 1 0
#> 124 9.73 1 NA 1 0
#> 32 20.90 1 37 1 0
#> 99 21.19 1 38 0 1
#> 30 17.43 1 78 0 0
#> 42 12.43 1 49 0 1
#> 29 15.45 1 68 1 0
#> 187.1 9.92 1 39 1 0
#> 155.1 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 79.1 16.23 1 54 1 0
#> 85 16.44 1 36 0 0
#> 99.1 21.19 1 38 0 1
#> 149 8.37 1 33 1 0
#> 199 19.81 1 NA 0 1
#> 39.1 15.59 1 37 0 1
#> 170.2 19.54 1 43 0 1
#> 68.1 20.62 1 44 0 0
#> 52 10.42 1 52 0 1
#> 150 20.33 1 48 0 0
#> 52.1 10.42 1 52 0 1
#> 36 21.19 1 48 0 1
#> 39.2 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 45 17.42 1 54 0 1
#> 183.2 9.24 1 67 1 0
#> 128 20.35 1 35 0 1
#> 179.1 18.63 1 42 0 0
#> 129 23.41 1 53 1 0
#> 16 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 105.1 19.75 1 60 0 0
#> 199.1 19.81 1 NA 0 1
#> 159.2 10.55 1 50 0 1
#> 183.3 9.24 1 67 1 0
#> 129.1 23.41 1 53 1 0
#> 24.1 23.89 1 38 0 0
#> 195.1 11.76 1 NA 1 0
#> 197 21.60 1 69 1 0
#> 199.2 19.81 1 NA 0 1
#> 179.2 18.63 1 42 0 0
#> 199.3 19.81 1 NA 0 1
#> 6 15.64 1 39 0 0
#> 187.2 9.92 1 39 1 0
#> 194 22.40 1 38 0 1
#> 8.1 18.43 1 32 0 0
#> 180.1 14.82 1 37 0 0
#> 136 21.83 1 43 0 1
#> 145.1 10.07 1 65 1 0
#> 139.1 21.49 1 63 1 0
#> 190 20.81 1 42 1 0
#> 199.4 19.81 1 NA 0 1
#> 139.2 21.49 1 63 1 0
#> 68.2 20.62 1 44 0 0
#> 36.1 21.19 1 48 0 1
#> 8.2 18.43 1 32 0 0
#> 43 12.10 1 61 0 1
#> 114 13.68 1 NA 0 0
#> 159.3 10.55 1 50 0 1
#> 134 17.81 1 47 1 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 26.1 15.77 1 49 0 1
#> 130.1 16.47 1 53 0 1
#> 153.1 21.33 1 55 1 0
#> 75 24.00 0 21 1 0
#> 17 24.00 0 38 0 1
#> 143 24.00 0 51 0 0
#> 27 24.00 0 63 1 0
#> 67 24.00 0 25 0 0
#> 173 24.00 0 19 0 1
#> 143.1 24.00 0 51 0 0
#> 116 24.00 0 58 0 1
#> 196 24.00 0 19 0 0
#> 33 24.00 0 53 0 0
#> 142 24.00 0 53 0 0
#> 11 24.00 0 42 0 1
#> 44 24.00 0 56 0 0
#> 104 24.00 0 50 1 0
#> 109 24.00 0 48 0 0
#> 20 24.00 0 46 1 0
#> 176 24.00 0 43 0 1
#> 3 24.00 0 31 1 0
#> 163 24.00 0 66 0 0
#> 46 24.00 0 71 0 0
#> 182 24.00 0 35 0 0
#> 2 24.00 0 9 0 0
#> 95 24.00 0 68 0 1
#> 83 24.00 0 6 0 0
#> 120 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 198 24.00 0 66 0 1
#> 135 24.00 0 58 1 0
#> 196.1 24.00 0 19 0 0
#> 2.1 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 87.1 24.00 0 27 0 0
#> 148 24.00 0 61 1 0
#> 83.1 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 34 24.00 0 36 0 0
#> 73 24.00 0 NA 0 1
#> 104.1 24.00 0 50 1 0
#> 151 24.00 0 42 0 0
#> 34.1 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 142.1 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 21 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 174 24.00 0 49 1 0
#> 137 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 34.2 24.00 0 36 0 0
#> 122 24.00 0 66 0 0
#> 196.2 24.00 0 19 0 0
#> 119 24.00 0 17 0 0
#> 53 24.00 0 32 0 1
#> 161 24.00 0 45 0 0
#> 12.1 24.00 0 63 0 0
#> 137.1 24.00 0 45 1 0
#> 72 24.00 0 40 0 1
#> 98 24.00 0 34 1 0
#> 84 24.00 0 39 0 1
#> 112 24.00 0 61 0 0
#> 144 24.00 0 28 0 1
#> 119.1 24.00 0 17 0 0
#> 115 24.00 0 NA 1 0
#> 80 24.00 0 41 0 0
#> 122.1 24.00 0 66 0 0
#> 109.1 24.00 0 48 0 0
#> 120.1 24.00 0 68 0 1
#> 121 24.00 0 57 1 0
#> 72.1 24.00 0 40 0 1
#> 182.1 24.00 0 35 0 0
#> 54 24.00 0 53 1 0
#> 165.1 24.00 0 47 0 0
#> 182.2 24.00 0 35 0 0
#> 46.1 24.00 0 71 0 0
#> 20.1 24.00 0 46 1 0
#> 87.2 24.00 0 27 0 0
#> 112.1 24.00 0 61 0 0
#> 20.2 24.00 0 46 1 0
#> 2.2 24.00 0 9 0 0
#> 27.1 24.00 0 63 1 0
#> 162 24.00 0 51 0 0
#> 165.2 24.00 0 47 0 0
#> 47.1 24.00 0 38 0 1
#> 102 24.00 0 49 0 0
#> 28 24.00 0 67 1 0
#> 46.2 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.06 NA NA NA
#> 2 age, Cure model 0.0150 NA NA NA
#> 3 grade_ii, Cure model 0.656 NA NA NA
#> 4 grade_iii, Cure model 1.23 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00110 NA NA NA
#> 2 grade_ii, Survival model 0.363 NA NA NA
#> 3 grade_iii, Survival model 0.486 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.0597 0.0150 0.6559 1.2301
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 258
#> Residual Deviance: 242.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.05971072 0.01500402 0.65589390 1.23008760
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001096246 0.363419540 0.486119277
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.65044944 0.74409908 0.31764355 0.04738329 0.73565130 0.38873691
#> [7] 0.96173503 0.98474389 0.45582798 0.49412238 0.81966352 0.87584642
#> [13] 0.85170131 0.52307791 0.71859702 0.36844423 0.61520246 0.79460535
#> [19] 0.11258494 0.58818685 0.56994570 0.12753952 0.78621328 0.81966352
#> [25] 0.77778991 0.75255037 0.19802684 0.06734452 0.67595280 0.91529874
#> [31] 0.99238717 0.56069855 0.54219098 0.01670541 0.72715155 0.42726207
#> [37] 0.70160200 0.59730267 0.69306068 0.62414685 0.89176494 0.38873691
#> [43] 0.96173503 0.91529874 0.97706960 0.29672371 0.25628901 0.50379618
#> [49] 0.80300442 0.68452464 0.89176494 0.75255037 0.23311196 0.59730267
#> [55] 0.56994570 0.25628901 0.95397346 0.65044944 0.38873691 0.31764355
#> [61] 0.85982912 0.35819081 0.85982912 0.25628901 0.65044944 0.41754978
#> [67] 0.51348524 0.91529874 0.34795242 0.42726207 0.08479252 0.94618737
#> [73] 0.15679626 0.36844423 0.81966352 0.91529874 0.08479252 0.01670541
#> [79] 0.18471036 0.42726207 0.64163825 0.89176494 0.14258647 0.45582798
#> [85] 0.70160200 0.17106645 0.87584642 0.19802684 0.30725011 0.19802684
#> [91] 0.31764355 0.25628901 0.45582798 0.81135624 0.81966352 0.48445631
#> [97] 0.53268197 0.76936862 0.62414685 0.54219098 0.23311196 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000
#>
#> $Time
#> 39 81 68 168 13 170 77 91 8 184 159 145 10
#> 15.59 14.06 20.62 23.72 14.34 19.54 7.27 5.33 18.43 17.77 10.55 10.07 10.53
#> 23 133 105 188 177 113 5 192 15 140 159.1 14 155
#> 16.92 14.65 19.75 16.16 12.53 22.86 16.43 16.44 22.68 12.68 10.55 12.89 13.08
#> 139 164 167 183 127 181 130 24 57 179 180 79 157
#> 21.49 23.60 15.55 9.24 3.53 16.46 16.47 23.89 14.46 18.63 14.82 16.23 15.10
#> 26 187 170.1 77.1 183.1 25 32 99 30 42 29 187.1 155.1
#> 15.77 9.92 19.54 7.27 9.24 6.32 20.90 21.19 17.43 12.43 15.45 9.92 13.08
#> 153 79.1 85 99.1 149 39.1 170.2 68.1 52 150 52.1 36 39.2
#> 21.33 16.23 16.44 21.19 8.37 15.59 19.54 20.62 10.42 20.33 10.42 21.19 15.59
#> 76 45 183.2 128 179.1 129 16 175 105.1 159.2 183.3 129.1 24.1
#> 19.22 17.42 9.24 20.35 18.63 23.41 8.71 21.91 19.75 10.55 9.24 23.41 23.89
#> 197 179.2 6 187.2 194 8.1 180.1 136 145.1 139.1 190 139.2 68.2
#> 21.60 18.63 15.64 9.92 22.40 18.43 14.82 21.83 10.07 21.49 20.81 21.49 20.62
#> 36.1 8.2 43 159.3 134 171 123 26.1 130.1 153.1 75 17 143
#> 21.19 18.43 12.10 10.55 17.81 16.57 13.00 15.77 16.47 21.33 24.00 24.00 24.00
#> 27 67 173 143.1 116 196 33 142 11 44 104 109 20
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 3 163 46 182 2 95 83 120 87 198 135 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 165 87.1 148 83.1 103 34 104.1 151 34.1 178 142.1 131
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 71 12 21 47 174 137 82 34.2 122 196.2 119 53 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12.1 137.1 72 98 84 112 144 119.1 80 122.1 109.1 120.1 121
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 72.1 182.1 54 165.1 182.2 46.1 20.1 87.2 112.1 20.2 2.2 27.1 162
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 47.1 102 28 46.2
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[81]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002120078 0.592366446 0.220113425
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.9750510 0.0349456 0.2951727
#> grade_iii, Cure model
#> 1.1149551
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 90 20.94 1 50 0 1
#> 70 7.38 1 30 1 0
#> 55 19.34 1 69 0 1
#> 177 12.53 1 75 0 0
#> 66 22.13 1 53 0 0
#> 56 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 108 18.29 1 39 0 1
#> 106 16.67 1 49 1 0
#> 199 19.81 1 NA 0 1
#> 66.1 22.13 1 53 0 0
#> 69 23.23 1 25 0 1
#> 136 21.83 1 43 0 1
#> 187 9.92 1 39 1 0
#> 99 21.19 1 38 0 1
#> 77 7.27 1 67 0 1
#> 140 12.68 1 59 1 0
#> 15 22.68 1 48 0 0
#> 170 19.54 1 43 0 1
#> 107 11.18 1 54 1 0
#> 177.1 12.53 1 75 0 0
#> 194 22.40 1 38 0 1
#> 168 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 169 22.41 1 46 0 0
#> 175 21.91 1 43 0 0
#> 169.1 22.41 1 46 0 0
#> 90.1 20.94 1 50 0 1
#> 150 20.33 1 48 0 0
#> 128 20.35 1 35 0 1
#> 136.1 21.83 1 43 0 1
#> 100 16.07 1 60 0 0
#> 42 12.43 1 49 0 1
#> 181 16.46 1 45 0 1
#> 129 23.41 1 53 1 0
#> 199.1 19.81 1 NA 0 1
#> 23 16.92 1 61 0 0
#> 170.1 19.54 1 43 0 1
#> 166 19.98 1 48 0 0
#> 39 15.59 1 37 0 1
#> 55.1 19.34 1 69 0 1
#> 78 23.88 1 43 0 0
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 36 21.19 1 48 0 1
#> 133 14.65 1 57 0 0
#> 167 15.55 1 56 1 0
#> 60 13.15 1 38 1 0
#> 180 14.82 1 37 0 0
#> 59 10.16 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 175.1 21.91 1 43 0 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 136.2 21.83 1 43 0 1
#> 181.1 16.46 1 45 0 1
#> 107.1 11.18 1 54 1 0
#> 111 17.45 1 47 0 1
#> 153 21.33 1 55 1 0
#> 197 21.60 1 69 1 0
#> 93 10.33 1 52 0 1
#> 139 21.49 1 63 1 0
#> 128.1 20.35 1 35 0 1
#> 49 12.19 1 48 1 0
#> 49.1 12.19 1 48 1 0
#> 158 20.14 1 74 1 0
#> 16 8.71 1 71 0 1
#> 175.2 21.91 1 43 0 0
#> 79 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 117 17.46 1 26 0 1
#> 150.1 20.33 1 48 0 0
#> 159 10.55 1 50 0 1
#> 45 17.42 1 54 0 1
#> 164 23.60 1 76 0 1
#> 30 17.43 1 78 0 0
#> 56.1 12.21 1 60 0 0
#> 32 20.90 1 37 1 0
#> 77.1 7.27 1 67 0 1
#> 197.1 21.60 1 69 1 0
#> 199.2 19.81 1 NA 0 1
#> 100.1 16.07 1 60 0 0
#> 101 9.97 1 10 0 1
#> 60.1 13.15 1 38 1 0
#> 154 12.63 1 20 1 0
#> 127 3.53 1 62 0 1
#> 5 16.43 1 51 0 1
#> 43 12.10 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 139.1 21.49 1 63 1 0
#> 180.1 14.82 1 37 0 0
#> 159.1 10.55 1 50 0 1
#> 197.2 21.60 1 69 1 0
#> 183 9.24 1 67 1 0
#> 13 14.34 1 54 0 1
#> 43.1 12.10 1 61 0 1
#> 15.1 22.68 1 48 0 0
#> 183.1 9.24 1 67 1 0
#> 133.1 14.65 1 57 0 0
#> 86.1 23.81 1 58 0 1
#> 55.2 19.34 1 69 0 1
#> 100.2 16.07 1 60 0 0
#> 134 17.81 1 47 1 0
#> 18 15.21 1 49 1 0
#> 194.1 22.40 1 38 0 1
#> 167.1 15.55 1 56 1 0
#> 39.1 15.59 1 37 0 1
#> 168.1 23.72 1 70 0 0
#> 56.2 12.21 1 60 0 0
#> 61 10.12 1 36 0 1
#> 110 17.56 1 65 0 1
#> 86.2 23.81 1 58 0 1
#> 1 24.00 0 23 1 0
#> 172 24.00 0 41 0 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 200 24.00 0 64 0 0
#> 83 24.00 0 6 0 0
#> 141 24.00 0 44 1 0
#> 151 24.00 0 42 0 0
#> 146 24.00 0 63 1 0
#> 137 24.00 0 45 1 0
#> 144 24.00 0 28 0 1
#> 19 24.00 0 57 0 1
#> 160 24.00 0 31 1 0
#> 12 24.00 0 63 0 0
#> 71 24.00 0 51 0 0
#> 71.1 24.00 0 51 0 0
#> 72 24.00 0 40 0 1
#> 53 24.00 0 32 0 1
#> 72.1 24.00 0 40 0 1
#> 72.2 24.00 0 40 0 1
#> 196 24.00 0 19 0 0
#> 131 24.00 0 66 0 0
#> 151.1 24.00 0 42 0 0
#> 35 24.00 0 51 0 0
#> 67 24.00 0 25 0 0
#> 22 24.00 0 52 1 0
#> 27 24.00 0 63 1 0
#> 141.1 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 67.1 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 144.1 24.00 0 28 0 1
#> 98 24.00 0 34 1 0
#> 17 24.00 0 38 0 1
#> 72.3 24.00 0 40 0 1
#> 178 24.00 0 52 1 0
#> 102 24.00 0 49 0 0
#> 104 24.00 0 50 1 0
#> 198 24.00 0 66 0 1
#> 112 24.00 0 61 0 0
#> 160.1 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 71.2 24.00 0 51 0 0
#> 137.1 24.00 0 45 1 0
#> 103 24.00 0 56 1 0
#> 198.1 24.00 0 66 0 1
#> 196.1 24.00 0 19 0 0
#> 174 24.00 0 49 1 0
#> 67.2 24.00 0 25 0 0
#> 160.2 24.00 0 31 1 0
#> 33.1 24.00 0 53 0 0
#> 54 24.00 0 53 1 0
#> 118 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 102.1 24.00 0 49 0 0
#> 34 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 144.2 24.00 0 28 0 1
#> 9 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 191 24.00 0 60 0 1
#> 196.2 24.00 0 19 0 0
#> 53.1 24.00 0 32 0 1
#> 191.1 24.00 0 60 0 1
#> 3 24.00 0 31 1 0
#> 84 24.00 0 39 0 1
#> 122 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 112.1 24.00 0 61 0 0
#> 34.1 24.00 0 36 0 0
#> 116.1 24.00 0 58 0 1
#> 19.1 24.00 0 57 0 1
#> 161 24.00 0 45 0 0
#> 185 24.00 0 44 1 0
#> 35.1 24.00 0 51 0 0
#> 72.4 24.00 0 40 0 1
#> 33.2 24.00 0 53 0 0
#> 122.1 24.00 0 66 0 0
#> 2 24.00 0 9 0 0
#> 103.1 24.00 0 56 1 0
#> 65 24.00 0 57 1 0
#> 112.2 24.00 0 61 0 0
#> 118.1 24.00 0 44 1 0
#> 62 24.00 0 71 0 0
#> 104.1 24.00 0 50 1 0
#> 104.2 24.00 0 50 1 0
#> 104.3 24.00 0 50 1 0
#> 147 24.00 0 76 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.98 NA NA NA
#> 2 age, Cure model 0.0349 NA NA NA
#> 3 grade_ii, Cure model 0.295 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00212 NA NA NA
#> 2 grade_ii, Survival model 0.592 NA NA NA
#> 3 grade_iii, Survival model 0.220 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.97505 0.03495 0.29517 1.11496
#>
#> Degrees of Freedom: 193 Total (i.e. Null); 190 Residual
#> Null Deviance: 267.3
#> Residual Deviance: 248.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.9750510 0.0349456 0.2951727 1.1149551
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002120078 0.592366446 0.220113425
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.371805909 0.968565158 0.483236286 0.798132386 0.208933238 0.822949586
#> [7] 0.133381115 0.510267657 0.582519273 0.208933238 0.109913786 0.262547264
#> [13] 0.936823971 0.352849009 0.976449055 0.781508985 0.144377358 0.464964258
#> [19] 0.880356642 0.798132386 0.187571266 0.060605374 0.121719358 0.165841837
#> [25] 0.230531653 0.165841837 0.371805909 0.427890631 0.409432662 0.262547264
#> [31] 0.635597048 0.814655917 0.600351546 0.097874523 0.573506589 0.464964258
#> [37] 0.455686043 0.661698597 0.483236286 0.009952829 0.029764155 0.739108155
#> [43] 0.352849009 0.721982122 0.679145817 0.756291105 0.704902223 0.230531653
#> [49] 0.591444983 0.773111822 0.262547264 0.600351546 0.880356642 0.546510229
#> [55] 0.343167231 0.294039687 0.912612820 0.323747872 0.409432662 0.847669109
#> [61] 0.847669109 0.446426077 0.960636289 0.230531653 0.626818354 0.400029968
#> [67] 0.537501964 0.427890631 0.896502262 0.564511056 0.084851953 0.555499528
#> [73] 0.822949586 0.390646925 0.976449055 0.294039687 0.635597048 0.928767512
#> [79] 0.756291105 0.789852749 0.992132718 0.617963687 0.864027561 0.323747872
#> [85] 0.704902223 0.896502262 0.294039687 0.944834634 0.747705129 0.864027561
#> [91] 0.144377358 0.944834634 0.721982122 0.029764155 0.483236286 0.635597048
#> [97] 0.519417847 0.696325691 0.187571266 0.679145817 0.661698597 0.060605374
#> [103] 0.822949586 0.920695645 0.528466540 0.029764155 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [193] 0.000000000 0.000000000
#>
#> $Time
#> 90 70 55 177 66 56 63 108 106 66.1 69 136 187
#> 20.94 7.38 19.34 12.53 22.13 12.21 22.77 18.29 16.67 22.13 23.23 21.83 9.92
#> 99 77 140 15 170 107 177.1 194 168 92 169 175 169.1
#> 21.19 7.27 12.68 22.68 19.54 11.18 12.53 22.40 23.72 22.92 22.41 21.91 22.41
#> 90.1 150 128 136.1 100 42 181 129 23 170.1 166 39 55.1
#> 20.94 20.33 20.35 21.83 16.07 12.43 16.46 23.41 16.92 19.54 19.98 15.59 19.34
#> 78 86 96 36 133 167 60 180 175.1 171 123 136.2 181.1
#> 23.88 23.81 14.54 21.19 14.65 15.55 13.15 14.82 21.91 16.57 13.00 21.83 16.46
#> 107.1 111 153 197 93 139 128.1 49 49.1 158 16 175.2 79
#> 11.18 17.45 21.33 21.60 10.33 21.49 20.35 12.19 12.19 20.14 8.71 21.91 16.23
#> 68 117 150.1 159 45 164 30 56.1 32 77.1 197.1 100.1 101
#> 20.62 17.46 20.33 10.55 17.42 23.60 17.43 12.21 20.90 7.27 21.60 16.07 9.97
#> 60.1 154 127 5 43 139.1 180.1 159.1 197.2 183 13 43.1 15.1
#> 13.15 12.63 3.53 16.43 12.10 21.49 14.82 10.55 21.60 9.24 14.34 12.10 22.68
#> 183.1 133.1 86.1 55.2 100.2 134 18 194.1 167.1 39.1 168.1 56.2 61
#> 9.24 14.65 23.81 19.34 16.07 17.81 15.21 22.40 15.55 15.59 23.72 12.21 10.12
#> 110 86.2 1 172 33 64 200 83 141 151 146 137 144
#> 17.56 23.81 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 19 160 12 71 71.1 72 53 72.1 72.2 196 131 151.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 22 27 141.1 21 67.1 132 144.1 98 17 72.3 178 102
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 198 112 160.1 116 71.2 137.1 103 198.1 196.1 174 67.2 160.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 54 118 44 102.1 34 152 144.2 9 87 191 196.2 53.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 3 84 122 74 112.1 34.1 116.1 19.1 161 185 35.1 72.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.2 122.1 2 103.1 65 112.2 118.1 62 104.1 104.2 104.3 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[82]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005877339 0.854017965 0.574524949
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -2.22728127 0.04155772 0.18547972
#> grade_iii, Cure model
#> 1.02793519
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 56 12.21 1 60 0 0
#> 194 22.40 1 38 0 1
#> 101 9.97 1 10 0 1
#> 168 23.72 1 70 0 0
#> 18 15.21 1 49 1 0
#> 13 14.34 1 54 0 1
#> 154 12.63 1 20 1 0
#> 113 22.86 1 34 0 0
#> 111 17.45 1 47 0 1
#> 89 11.44 1 NA 0 0
#> 183 9.24 1 67 1 0
#> 136 21.83 1 43 0 1
#> 42 12.43 1 49 0 1
#> 197 21.60 1 69 1 0
#> 18.1 15.21 1 49 1 0
#> 43 12.10 1 61 0 1
#> 41 18.02 1 40 1 0
#> 168.1 23.72 1 70 0 0
#> 171 16.57 1 41 0 1
#> 189 10.51 1 NA 1 0
#> 194.1 22.40 1 38 0 1
#> 190 20.81 1 42 1 0
#> 70 7.38 1 30 1 0
#> 10 10.53 1 34 0 0
#> 168.2 23.72 1 70 0 0
#> 78 23.88 1 43 0 0
#> 194.2 22.40 1 38 0 1
#> 123 13.00 1 44 1 0
#> 110 17.56 1 65 0 1
#> 189.1 10.51 1 NA 1 0
#> 18.2 15.21 1 49 1 0
#> 133 14.65 1 57 0 0
#> 89.1 11.44 1 NA 0 0
#> 111.1 17.45 1 47 0 1
#> 77 7.27 1 67 0 1
#> 76 19.22 1 54 0 1
#> 16 8.71 1 71 0 1
#> 197.1 21.60 1 69 1 0
#> 111.2 17.45 1 47 0 1
#> 195 11.76 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 170 19.54 1 43 0 1
#> 23 16.92 1 61 0 0
#> 91 5.33 1 61 0 1
#> 197.2 21.60 1 69 1 0
#> 181 16.46 1 45 0 1
#> 124 9.73 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 37 12.52 1 57 1 0
#> 5 16.43 1 51 0 1
#> 8 18.43 1 32 0 0
#> 90 20.94 1 50 0 1
#> 61 10.12 1 36 0 1
#> 197.3 21.60 1 69 1 0
#> 136.1 21.83 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 36.1 21.19 1 48 0 1
#> 59 10.16 1 NA 1 0
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 50 10.02 1 NA 1 0
#> 158 20.14 1 74 1 0
#> 89.2 11.44 1 NA 0 0
#> 29 15.45 1 68 1 0
#> 194.3 22.40 1 38 0 1
#> 188.1 16.16 1 46 0 1
#> 37.1 12.52 1 57 1 0
#> 105 19.75 1 60 0 0
#> 37.2 12.52 1 57 1 0
#> 43.1 12.10 1 61 0 1
#> 42.1 12.43 1 49 0 1
#> 93 10.33 1 52 0 1
#> 149 8.37 1 33 1 0
#> 56.1 12.21 1 60 0 0
#> 63 22.77 1 31 1 0
#> 49 12.19 1 48 1 0
#> 57 14.46 1 45 0 1
#> 45 17.42 1 54 0 1
#> 42.2 12.43 1 49 0 1
#> 153 21.33 1 55 1 0
#> 10.1 10.53 1 34 0 0
#> 58 19.34 1 39 0 0
#> 130 16.47 1 53 0 1
#> 140 12.68 1 59 1 0
#> 50.1 10.02 1 NA 1 0
#> 5.1 16.43 1 51 0 1
#> 13.1 14.34 1 54 0 1
#> 108 18.29 1 39 0 1
#> 159 10.55 1 50 0 1
#> 55 19.34 1 69 0 1
#> 105.1 19.75 1 60 0 0
#> 15 22.68 1 48 0 0
#> 60 13.15 1 38 1 0
#> 145 10.07 1 65 1 0
#> 181.1 16.46 1 45 0 1
#> 150 20.33 1 48 0 0
#> 140.1 12.68 1 59 1 0
#> 81 14.06 1 34 0 0
#> 56.2 12.21 1 60 0 0
#> 187 9.92 1 39 1 0
#> 101.1 9.97 1 10 0 1
#> 136.2 21.83 1 43 0 1
#> 105.2 19.75 1 60 0 0
#> 107 11.18 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 66 22.13 1 53 0 0
#> 145.1 10.07 1 65 1 0
#> 30 17.43 1 78 0 0
#> 136.3 21.83 1 43 0 1
#> 14 12.89 1 21 0 0
#> 168.3 23.72 1 70 0 0
#> 105.3 19.75 1 60 0 0
#> 73 24.00 0 NA 0 1
#> 19 24.00 0 57 0 1
#> 135 24.00 0 58 1 0
#> 178 24.00 0 52 1 0
#> 118 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 146 24.00 0 63 1 0
#> 17 24.00 0 38 0 1
#> 34 24.00 0 36 0 0
#> 72 24.00 0 40 0 1
#> 176 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 198 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 121.1 24.00 0 57 1 0
#> 185 24.00 0 44 1 0
#> 98 24.00 0 34 1 0
#> 161 24.00 0 45 0 0
#> 67 24.00 0 25 0 0
#> 34.1 24.00 0 36 0 0
#> 116 24.00 0 58 0 1
#> 11 24.00 0 42 0 1
#> 172 24.00 0 41 0 0
#> 143 24.00 0 51 0 0
#> 72.1 24.00 0 40 0 1
#> 21 24.00 0 47 0 0
#> 126 24.00 0 48 0 0
#> 72.2 24.00 0 40 0 1
#> 146.1 24.00 0 63 1 0
#> 161.1 24.00 0 45 0 0
#> 82 24.00 0 34 0 0
#> 87 24.00 0 27 0 0
#> 21.1 24.00 0 47 0 0
#> 151 24.00 0 42 0 0
#> 160 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 2 24.00 0 9 0 0
#> 115 24.00 0 NA 1 0
#> 74 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 21.2 24.00 0 47 0 0
#> 48 24.00 0 31 1 0
#> 62 24.00 0 71 0 0
#> 54 24.00 0 53 1 0
#> 115.1 24.00 0 NA 1 0
#> 121.2 24.00 0 57 1 0
#> 144 24.00 0 28 0 1
#> 103 24.00 0 56 1 0
#> 9 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 103.1 24.00 0 56 1 0
#> 144.1 24.00 0 28 0 1
#> 47 24.00 0 38 0 1
#> 109.1 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 80 24.00 0 41 0 0
#> 103.2 24.00 0 56 1 0
#> 141 24.00 0 44 1 0
#> 165.1 24.00 0 47 0 0
#> 121.3 24.00 0 57 1 0
#> 47.1 24.00 0 38 0 1
#> 131 24.00 0 66 0 0
#> 83 24.00 0 6 0 0
#> 143.1 24.00 0 51 0 0
#> 176.1 24.00 0 43 0 1
#> 71 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 176.2 24.00 0 43 0 1
#> 7.1 24.00 0 37 1 0
#> 144.2 24.00 0 28 0 1
#> 152 24.00 0 36 0 1
#> 98.1 24.00 0 34 1 0
#> 28 24.00 0 67 1 0
#> 82.1 24.00 0 34 0 0
#> 147 24.00 0 76 1 0
#> 152.1 24.00 0 36 0 1
#> 48.1 24.00 0 31 1 0
#> 176.3 24.00 0 43 0 1
#> 109.2 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 82.2 24.00 0 34 0 0
#> 53 24.00 0 32 0 1
#> 64 24.00 0 43 0 0
#> 103.3 24.00 0 56 1 0
#> 118.1 24.00 0 44 1 0
#> 126.1 24.00 0 48 0 0
#> 72.3 24.00 0 40 0 1
#> 193 24.00 0 45 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -2.23 NA NA NA
#> 2 age, Cure model 0.0416 NA NA NA
#> 3 grade_ii, Cure model 0.185 NA NA NA
#> 4 grade_iii, Cure model 1.03 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00588 NA NA NA
#> 2 grade_ii, Survival model 0.854 NA NA NA
#> 3 grade_iii, Survival model 0.575 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -2.22728 0.04156 0.18548 1.02794
#>
#> Degrees of Freedom: 186 Total (i.e. Null); 183 Residual
#> Null Deviance: 257.7
#> Residual Deviance: 239.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -2.22728127 0.04155772 0.18547972 1.02793519
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005877339 0.854017965 0.574524949
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.819071717 0.131610173 0.931067932 0.023865591 0.641127977 0.693595936
#> [7] 0.762389289 0.076665997 0.482327557 0.954311482 0.194617959 0.795033113
#> [13] 0.240511117 0.641127977 0.851423473 0.462845806 0.023865591 0.548505236
#> [19] 0.131610173 0.323477759 0.977321886 0.883474667 0.023865591 0.006585747
#> [25] 0.131610173 0.728384033 0.472607986 0.641127977 0.675947240 0.482327557
#> [31] 0.984893553 0.432877432 0.962007439 0.240511117 0.482327557 0.292659593
#> [37] 0.393107496 0.529424856 0.992453706 0.240511117 0.567572709 0.622906541
#> [43] 0.770750975 0.586206883 0.442871280 0.313163486 0.907420113 0.240511117
#> [49] 0.194617959 0.529424856 0.292659593 0.667135054 0.604655663 0.343646239
#> [55] 0.632055023 0.131610173 0.604655663 0.770750975 0.353615138 0.770750975
#> [61] 0.851423473 0.795033113 0.899429145 0.969692927 0.819071717 0.097023359
#> [67] 0.843321855 0.684792253 0.519901517 0.795033113 0.281962674 0.883474667
#> [73] 0.412987409 0.558063471 0.745557787 0.586206883 0.693595936 0.452903951
#> [79] 0.875487333 0.412987409 0.353615138 0.113992527 0.719719903 0.915380410
#> [85] 0.567572709 0.333524517 0.745557787 0.710963126 0.819071717 0.946579082
#> [91] 0.931067932 0.194617959 0.353615138 0.867476320 0.393107496 0.180596466
#> [97] 0.915380410 0.510326754 0.194617959 0.736965101 0.023865591 0.353615138
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000
#>
#> $Time
#> 56 194 101 168 18 13 154 113 111 183 136 42 197
#> 12.21 22.40 9.97 23.72 15.21 14.34 12.63 22.86 17.45 9.24 21.83 12.43 21.60
#> 18.1 43 41 168.1 171 194.1 190 70 10 168.2 78 194.2 123
#> 15.21 12.10 18.02 23.72 16.57 22.40 20.81 7.38 10.53 23.72 23.88 22.40 13.00
#> 110 18.2 133 111.1 77 76 16 197.1 111.2 36 170 23 91
#> 17.56 15.21 14.65 17.45 7.27 19.22 8.71 21.60 17.45 21.19 19.54 16.92 5.33
#> 197.2 181 26 37 5 8 90 61 197.3 136.1 23.1 36.1 157
#> 21.60 16.46 15.77 12.52 16.43 18.43 20.94 10.12 21.60 21.83 16.92 21.19 15.10
#> 188 158 29 194.3 188.1 37.1 105 37.2 43.1 42.1 93 149 56.1
#> 16.16 20.14 15.45 22.40 16.16 12.52 19.75 12.52 12.10 12.43 10.33 8.37 12.21
#> 63 49 57 45 42.2 153 10.1 58 130 140 5.1 13.1 108
#> 22.77 12.19 14.46 17.42 12.43 21.33 10.53 19.34 16.47 12.68 16.43 14.34 18.29
#> 159 55 105.1 15 60 145 181.1 150 140.1 81 56.2 187 101.1
#> 10.55 19.34 19.75 22.68 13.15 10.07 16.46 20.33 12.68 14.06 12.21 9.92 9.97
#> 136.2 105.2 107 170.1 66 145.1 30 136.3 14 168.3 105.3 19 135
#> 21.83 19.75 11.18 19.54 22.13 10.07 17.43 21.83 12.89 23.72 19.75 24.00 24.00
#> 178 118 35 146 17 34 72 176 112 198 121 121.1 185
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 98 161 67 34.1 116 11 172 143 72.1 21 126 72.2 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 161.1 82 87 21.1 151 160 109 2 74 165 21.2 48 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 54 121.2 144 103 9 112.1 103.1 144.1 47 109.1 7 80 103.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 165.1 121.3 47.1 131 83 143.1 176.1 71 182 176.2 7.1 144.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152 98.1 28 82.1 147 152.1 48.1 176.3 109.2 31 82.2 53 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.3 118.1 126.1 72.3 193
#> 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[83]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.02262888 0.34087737 0.18093176
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.055121587 0.007282421 -0.748318346
#> grade_iii, Cure model
#> 0.159473462
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 197 21.60 1 69 1 0
#> 127 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 153 21.33 1 55 1 0
#> 8 18.43 1 32 0 0
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 6 15.64 1 39 0 0
#> 188 16.16 1 46 0 1
#> 57 14.46 1 45 0 1
#> 168 23.72 1 70 0 0
#> 134 17.81 1 47 1 0
#> 63 22.77 1 31 1 0
#> 114 13.68 1 NA 0 0
#> 150 20.33 1 48 0 0
#> 26 15.77 1 49 0 1
#> 86 23.81 1 58 0 1
#> 123 13.00 1 44 1 0
#> 25 6.32 1 34 1 0
#> 180 14.82 1 37 0 0
#> 56 12.21 1 60 0 0
#> 85 16.44 1 36 0 0
#> 13 14.34 1 54 0 1
#> 171 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 18 15.21 1 49 1 0
#> 184 17.77 1 38 0 0
#> 181 16.46 1 45 0 1
#> 101 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 124 9.73 1 NA 1 0
#> 100.1 16.07 1 60 0 0
#> 189 10.51 1 NA 1 0
#> 111 17.45 1 47 0 1
#> 168.1 23.72 1 70 0 0
#> 175 21.91 1 43 0 0
#> 10 10.53 1 34 0 0
#> 107 11.18 1 54 1 0
#> 81 14.06 1 34 0 0
#> 85.1 16.44 1 36 0 0
#> 96 14.54 1 33 0 1
#> 168.2 23.72 1 70 0 0
#> 107.1 11.18 1 54 1 0
#> 60 13.15 1 38 1 0
#> 159 10.55 1 50 0 1
#> 81.1 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 99 21.19 1 38 0 1
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 117 17.46 1 26 0 1
#> 4 17.64 1 NA 0 1
#> 39 15.59 1 37 0 1
#> 180.1 14.82 1 37 0 0
#> 81.2 14.06 1 34 0 0
#> 129 23.41 1 53 1 0
#> 23 16.92 1 61 0 0
#> 8.1 18.43 1 32 0 0
#> 114.1 13.68 1 NA 0 0
#> 5.1 16.43 1 51 0 1
#> 18.1 15.21 1 49 1 0
#> 188.1 16.16 1 46 0 1
#> 30 17.43 1 78 0 0
#> 96.1 14.54 1 33 0 1
#> 171.1 16.57 1 41 0 1
#> 24 23.89 1 38 0 0
#> 179.1 18.63 1 42 0 0
#> 57.1 14.46 1 45 0 1
#> 164 23.60 1 76 0 1
#> 188.2 16.16 1 46 0 1
#> 136 21.83 1 43 0 1
#> 171.2 16.57 1 41 0 1
#> 168.3 23.72 1 70 0 0
#> 183 9.24 1 67 1 0
#> 51 18.23 1 83 0 1
#> 130 16.47 1 53 0 1
#> 140 12.68 1 59 1 0
#> 149 8.37 1 33 1 0
#> 177 12.53 1 75 0 0
#> 180.2 14.82 1 37 0 0
#> 188.3 16.16 1 46 0 1
#> 79.1 16.23 1 54 1 0
#> 117.1 17.46 1 26 0 1
#> 66 22.13 1 53 0 0
#> 15 22.68 1 48 0 0
#> 199.1 19.81 1 NA 0 1
#> 150.1 20.33 1 48 0 0
#> 153.1 21.33 1 55 1 0
#> 45 17.42 1 54 0 1
#> 153.2 21.33 1 55 1 0
#> 139 21.49 1 63 1 0
#> 128 20.35 1 35 0 1
#> 188.4 16.16 1 46 0 1
#> 85.2 16.44 1 36 0 0
#> 32 20.90 1 37 1 0
#> 190 20.81 1 42 1 0
#> 155 13.08 1 26 0 0
#> 92 22.92 1 47 0 1
#> 10.1 10.53 1 34 0 0
#> 117.2 17.46 1 26 0 1
#> 6.1 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 164.1 23.60 1 76 0 1
#> 125 15.65 1 67 1 0
#> 181.1 16.46 1 45 0 1
#> 40 18.00 1 28 1 0
#> 86.1 23.81 1 58 0 1
#> 188.5 16.16 1 46 0 1
#> 16 8.71 1 71 0 1
#> 167.1 15.55 1 56 1 0
#> 195 11.76 1 NA 1 0
#> 97 19.14 1 65 0 1
#> 174 24.00 0 49 1 0
#> 22 24.00 0 52 1 0
#> 152 24.00 0 36 0 1
#> 28 24.00 0 67 1 0
#> 21 24.00 0 47 0 0
#> 131 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 19 24.00 0 57 0 1
#> 3 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 103 24.00 0 56 1 0
#> 151 24.00 0 42 0 0
#> 22.1 24.00 0 52 1 0
#> 9 24.00 0 31 1 0
#> 118 24.00 0 44 1 0
#> 67 24.00 0 25 0 0
#> 137 24.00 0 45 1 0
#> 118.1 24.00 0 44 1 0
#> 120.1 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 12 24.00 0 63 0 0
#> 191 24.00 0 60 0 1
#> 137.1 24.00 0 45 1 0
#> 186 24.00 0 45 1 0
#> 21.1 24.00 0 47 0 0
#> 47 24.00 0 38 0 1
#> 67.1 24.00 0 25 0 0
#> 71 24.00 0 51 0 0
#> 156 24.00 0 50 1 0
#> 143 24.00 0 51 0 0
#> 82 24.00 0 34 0 0
#> 98 24.00 0 34 1 0
#> 9.1 24.00 0 31 1 0
#> 185 24.00 0 44 1 0
#> 21.2 24.00 0 47 0 0
#> 19.1 24.00 0 57 0 1
#> 132 24.00 0 55 0 0
#> 186.1 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 54 24.00 0 53 1 0
#> 3.1 24.00 0 31 1 0
#> 176 24.00 0 43 0 1
#> 44 24.00 0 56 0 0
#> 144 24.00 0 28 0 1
#> 46 24.00 0 71 0 0
#> 38 24.00 0 31 1 0
#> 120.2 24.00 0 68 0 1
#> 174.1 24.00 0 49 1 0
#> 48 24.00 0 31 1 0
#> 27 24.00 0 63 1 0
#> 163 24.00 0 66 0 0
#> 17 24.00 0 38 0 1
#> 27.1 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 102 24.00 0 49 0 0
#> 22.2 24.00 0 52 1 0
#> 54.1 24.00 0 53 1 0
#> 174.2 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 138 24.00 0 44 1 0
#> 65 24.00 0 57 1 0
#> 144.1 24.00 0 28 0 1
#> 147 24.00 0 76 1 0
#> 141 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 34 24.00 0 36 0 0
#> 19.2 24.00 0 57 0 1
#> 142.1 24.00 0 53 0 0
#> 12.1 24.00 0 63 0 0
#> 176.1 24.00 0 43 0 1
#> 83 24.00 0 6 0 0
#> 28.1 24.00 0 67 1 0
#> 116 24.00 0 58 0 1
#> 118.2 24.00 0 44 1 0
#> 138.1 24.00 0 44 1 0
#> 176.2 24.00 0 43 0 1
#> 48.1 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 72 24.00 0 40 0 1
#> 173.1 24.00 0 19 0 1
#> 147.1 24.00 0 76 1 0
#> 131.1 24.00 0 66 0 0
#> 176.3 24.00 0 43 0 1
#> 17.1 24.00 0 38 0 1
#> 83.1 24.00 0 6 0 0
#> 31 24.00 0 36 0 1
#> 44.1 24.00 0 56 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.0551 NA NA NA
#> 2 age, Cure model 0.00728 NA NA NA
#> 3 grade_ii, Cure model -0.748 NA NA NA
#> 4 grade_iii, Cure model 0.159 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0226 NA NA NA
#> 2 grade_ii, Survival model 0.341 NA NA NA
#> 3 grade_iii, Survival model 0.181 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.055122 0.007282 -0.748318 0.159473
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 261.7
#> Residual Deviance: 254.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.055121587 0.007282421 -0.748318346 0.159473462
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.02262888 0.34087737 0.18093176
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 8.488465e-03 9.773208e-01 4.307613e-02 1.199663e-02 5.130999e-02
#> [6] 3.561906e-02 3.572171e-01 2.438111e-01 5.319896e-01 7.154874e-05
#> [11] 7.579300e-02 2.786151e-03 2.919034e-02 3.316545e-01 1.100338e-05
#> [16] 6.695792e-01 9.332025e-01 4.548137e-01 7.258512e-01 1.783728e-01
#> [21] 5.647601e-01 1.314333e-01 3.074459e-01 4.256295e-01 8.133768e-02
#> [26] 1.617313e-01 8.470425e-01 2.237839e-01 3.074459e-01 1.043837e-01
#> [31] 7.154874e-05 5.728643e-03 8.055524e-01 7.453722e-01 5.817132e-01
#> [36] 1.783728e-01 5.003255e-01 7.154874e-05 7.453722e-01 6.334642e-01
#> [41] 7.851060e-01 5.817132e-01 2.047545e-01 1.822849e-02 9.332025e-01
#> [46] 6.028780e-02 8.710936e-02 3.837457e-01 4.548137e-01 5.817132e-01
#> [51] 1.409255e-03 1.242421e-01 5.130999e-02 2.047545e-01 4.256295e-01
#> [56] 2.438111e-01 1.107094e-01 5.003255e-01 1.314333e-01 1.035914e-06
#> [61] 4.307613e-02 5.319896e-01 5.946947e-04 2.438111e-01 7.034523e-03
#> [66] 1.314333e-01 7.154874e-05 8.680711e-01 6.520713e-02 1.536686e-01
#> [71] 6.879880e-01 9.112426e-01 7.067125e-01 4.548137e-01 2.438111e-01
#> [76] 2.237839e-01 8.710936e-02 4.585272e-03 3.611804e-03 2.919034e-02
#> [81] 1.199663e-02 1.173496e-01 1.199663e-02 1.014233e-02 2.623644e-02
#> [86] 2.438111e-01 1.783728e-01 2.076415e-02 2.342733e-02 6.514104e-01
#> [91] 2.029455e-03 8.055524e-01 8.710936e-02 3.572171e-01 3.974802e-01
#> [96] 5.946947e-04 3.442718e-01 1.617313e-01 7.044954e-02 1.100338e-05
#> [101] 2.438111e-01 8.894579e-01 3.974802e-01 3.921926e-02 0.000000e+00
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 197 127 179 153 8 166 6 188 57 168 134 63 150
#> 21.60 3.53 18.63 21.33 18.43 19.98 15.64 16.16 14.46 23.72 17.81 22.77 20.33
#> 26 86 123 25 180 56 85 13 171 100 18 184 181
#> 15.77 23.81 13.00 6.32 14.82 12.21 16.44 14.34 16.57 16.07 15.21 17.77 16.46
#> 101 79 100.1 111 168.1 175 10 107 81 85.1 96 168.2 107.1
#> 9.97 16.23 16.07 17.45 23.72 21.91 10.53 11.18 14.06 16.44 14.54 23.72 11.18
#> 60 159 81.1 5 99 25.1 88 117 39 180.1 81.2 129 23
#> 13.15 10.55 14.06 16.43 21.19 6.32 18.37 17.46 15.59 14.82 14.06 23.41 16.92
#> 8.1 5.1 18.1 188.1 30 96.1 171.1 24 179.1 57.1 164 188.2 136
#> 18.43 16.43 15.21 16.16 17.43 14.54 16.57 23.89 18.63 14.46 23.60 16.16 21.83
#> 171.2 168.3 183 51 130 140 149 177 180.2 188.3 79.1 117.1 66
#> 16.57 23.72 9.24 18.23 16.47 12.68 8.37 12.53 14.82 16.16 16.23 17.46 22.13
#> 15 150.1 153.1 45 153.2 139 128 188.4 85.2 32 190 155 92
#> 22.68 20.33 21.33 17.42 21.33 21.49 20.35 16.16 16.44 20.90 20.81 13.08 22.92
#> 10.1 117.2 6.1 167 164.1 125 181.1 40 86.1 188.5 16 167.1 97
#> 10.53 17.46 15.64 15.55 23.60 15.65 16.46 18.00 23.81 16.16 8.71 15.55 19.14
#> 174 22 152 28 21 131 120 173 19 3 196 103 151
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 22.1 9 118 67 137 118.1 120.1 104 12 191 137.1 186 21.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47 67.1 71 156 143 82 98 9.1 185 21.2 19.1 132 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 75 54 3.1 176 44 144 46 38 120.2 174.1 48 27 163
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 27.1 95 102 22.2 54.1 174.2 142 138 65 144.1 147 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34 19.2 142.1 12.1 176.1 83 28.1 116 118.2 138.1 176.2 48.1 72
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 173.1 147.1 131.1 176.3 17.1 83.1 31 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[84]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.007398091 0.377438624 0.239873323
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.91890437 0.01681006 0.30927561
#> grade_iii, Cure model
#> 0.52697447
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 159 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 88 18.37 1 47 0 0
#> 23 16.92 1 61 0 0
#> 181 16.46 1 45 0 1
#> 107 11.18 1 54 1 0
#> 50 10.02 1 NA 1 0
#> 195 11.76 1 NA 1 0
#> 29 15.45 1 68 1 0
#> 125 15.65 1 67 1 0
#> 55 19.34 1 69 0 1
#> 111 17.45 1 47 0 1
#> 180 14.82 1 37 0 0
#> 42 12.43 1 49 0 1
#> 105 19.75 1 60 0 0
#> 180.1 14.82 1 37 0 0
#> 123 13.00 1 44 1 0
#> 127 3.53 1 62 0 1
#> 129 23.41 1 53 1 0
#> 96 14.54 1 33 0 1
#> 45 17.42 1 54 0 1
#> 29.1 15.45 1 68 1 0
#> 179 18.63 1 42 0 0
#> 52 10.42 1 52 0 1
#> 181.1 16.46 1 45 0 1
#> 197 21.60 1 69 1 0
#> 58 19.34 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 190 20.81 1 42 1 0
#> 57 14.46 1 45 0 1
#> 167 15.55 1 56 1 0
#> 52.1 10.42 1 52 0 1
#> 81 14.06 1 34 0 0
#> 68 20.62 1 44 0 0
#> 56 12.21 1 60 0 0
#> 57.1 14.46 1 45 0 1
#> 56.1 12.21 1 60 0 0
#> 57.2 14.46 1 45 0 1
#> 130.1 16.47 1 53 0 1
#> 88.1 18.37 1 47 0 0
#> 18 15.21 1 49 1 0
#> 110 17.56 1 65 0 1
#> 166 19.98 1 48 0 0
#> 60 13.15 1 38 1 0
#> 167.1 15.55 1 56 1 0
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 66 22.13 1 53 0 0
#> 26 15.77 1 49 0 1
#> 189.1 10.51 1 NA 1 0
#> 107.1 11.18 1 54 1 0
#> 92 22.92 1 47 0 1
#> 167.2 15.55 1 56 1 0
#> 37 12.52 1 57 1 0
#> 155 13.08 1 26 0 0
#> 37.1 12.52 1 57 1 0
#> 125.1 15.65 1 67 1 0
#> 171 16.57 1 41 0 1
#> 175 21.91 1 43 0 0
#> 179.1 18.63 1 42 0 0
#> 199 19.81 1 NA 0 1
#> 125.2 15.65 1 67 1 0
#> 195.1 11.76 1 NA 1 0
#> 23.1 16.92 1 61 0 0
#> 10 10.53 1 34 0 0
#> 187 9.92 1 39 1 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 140 12.68 1 59 1 0
#> 49 12.19 1 48 1 0
#> 188 16.16 1 46 0 1
#> 36 21.19 1 48 0 1
#> 91 5.33 1 61 0 1
#> 171.1 16.57 1 41 0 1
#> 100 16.07 1 60 0 0
#> 89 11.44 1 NA 0 0
#> 23.2 16.92 1 61 0 0
#> 86 23.81 1 58 0 1
#> 59 10.16 1 NA 1 0
#> 77 7.27 1 67 0 1
#> 105.1 19.75 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 36.1 21.19 1 48 0 1
#> 159.1 10.55 1 50 0 1
#> 30 17.43 1 78 0 0
#> 36.2 21.19 1 48 0 1
#> 77.1 7.27 1 67 0 1
#> 101 9.97 1 10 0 1
#> 60.1 13.15 1 38 1 0
#> 133 14.65 1 57 0 0
#> 4 17.64 1 NA 0 1
#> 52.2 10.42 1 52 0 1
#> 192 16.44 1 31 1 0
#> 66.1 22.13 1 53 0 0
#> 192.1 16.44 1 31 1 0
#> 108 18.29 1 39 0 1
#> 61 10.12 1 36 0 1
#> 106 16.67 1 49 1 0
#> 155.1 13.08 1 26 0 0
#> 14.1 12.89 1 21 0 0
#> 13.1 14.34 1 54 0 1
#> 85 16.44 1 36 0 0
#> 61.1 10.12 1 36 0 1
#> 32 20.90 1 37 1 0
#> 6 15.64 1 39 0 0
#> 190.1 20.81 1 42 1 0
#> 128.1 20.35 1 35 0 1
#> 15.1 22.68 1 48 0 0
#> 16 8.71 1 71 0 1
#> 67 24.00 0 25 0 0
#> 200 24.00 0 64 0 0
#> 53 24.00 0 32 0 1
#> 53.1 24.00 0 32 0 1
#> 200.1 24.00 0 64 0 0
#> 193 24.00 0 45 0 1
#> 182 24.00 0 35 0 0
#> 31 24.00 0 36 0 1
#> 54 24.00 0 53 1 0
#> 132 24.00 0 55 0 0
#> 67.1 24.00 0 25 0 0
#> 142 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 165 24.00 0 47 0 0
#> 7 24.00 0 37 1 0
#> 144 24.00 0 28 0 1
#> 62 24.00 0 71 0 0
#> 109 24.00 0 48 0 0
#> 173 24.00 0 19 0 1
#> 35 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 54.1 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 47 24.00 0 38 0 1
#> 112 24.00 0 61 0 0
#> 148.1 24.00 0 61 1 0
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 35.1 24.00 0 51 0 0
#> 143 24.00 0 51 0 0
#> 176 24.00 0 43 0 1
#> 198 24.00 0 66 0 1
#> 163 24.00 0 66 0 0
#> 131 24.00 0 66 0 0
#> 173.1 24.00 0 19 0 1
#> 198.1 24.00 0 66 0 1
#> 132.1 24.00 0 55 0 0
#> 73 24.00 0 NA 0 1
#> 198.2 24.00 0 66 0 1
#> 191 24.00 0 60 0 1
#> 54.2 24.00 0 53 1 0
#> 152 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 75 24.00 0 21 1 0
#> 72 24.00 0 40 0 1
#> 65 24.00 0 57 1 0
#> 12 24.00 0 63 0 0
#> 200.2 24.00 0 64 0 0
#> 22 24.00 0 52 1 0
#> 196 24.00 0 19 0 0
#> 34.1 24.00 0 36 0 0
#> 196.1 24.00 0 19 0 0
#> 84 24.00 0 39 0 1
#> 31.1 24.00 0 36 0 1
#> 1 24.00 0 23 1 0
#> 62.1 24.00 0 71 0 0
#> 98 24.00 0 34 1 0
#> 84.1 24.00 0 39 0 1
#> 102.1 24.00 0 49 0 0
#> 185 24.00 0 44 1 0
#> 98.1 24.00 0 34 1 0
#> 193.1 24.00 0 45 0 1
#> 196.2 24.00 0 19 0 0
#> 162 24.00 0 51 0 0
#> 196.3 24.00 0 19 0 0
#> 34.2 24.00 0 36 0 0
#> 95.1 24.00 0 68 0 1
#> 84.2 24.00 0 39 0 1
#> 48 24.00 0 31 1 0
#> 74 24.00 0 43 0 1
#> 9 24.00 0 31 1 0
#> 46 24.00 0 71 0 0
#> 137 24.00 0 45 1 0
#> 35.2 24.00 0 51 0 0
#> 109.1 24.00 0 48 0 0
#> 7.1 24.00 0 37 1 0
#> 103 24.00 0 56 1 0
#> 152.1 24.00 0 36 0 1
#> 198.3 24.00 0 66 0 1
#> 112.1 24.00 0 61 0 0
#> 65.1 24.00 0 57 1 0
#> 173.2 24.00 0 19 0 1
#> 160 24.00 0 31 1 0
#> 162.1 24.00 0 51 0 0
#> 53.2 24.00 0 32 0 1
#> 95.2 24.00 0 68 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.919 NA NA NA
#> 2 age, Cure model 0.0168 NA NA NA
#> 3 grade_ii, Cure model 0.309 NA NA NA
#> 4 grade_iii, Cure model 0.527 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00740 NA NA NA
#> 2 grade_ii, Survival model 0.377 NA NA NA
#> 3 grade_iii, Survival model 0.240 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91890 0.01681 0.30928 0.52697
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 256.1 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.91890437 0.01681006 0.30927561 0.52697447
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.007398091 0.377438624 0.239873323
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.832697995 0.124758338 0.210364145 0.286175825 0.366139908 0.810674132
#> [7] 0.519798359 0.447569650 0.166056128 0.256993888 0.551340998 0.766602892
#> [13] 0.149110965 0.551340998 0.701303745 0.988684964 0.007754095 0.583237390
#> [19] 0.276362981 0.519798359 0.192404848 0.865945313 0.366139908 0.061741782
#> [25] 0.166056128 0.345905634 0.625789902 0.100916702 0.593982685 0.488821445
#> [31] 0.865945313 0.647286988 0.116518340 0.777577489 0.593982685 0.777577489
#> [37] 0.593982685 0.345905634 0.210364145 0.540759802 0.238208709 0.140735376
#> [43] 0.658166808 0.488821445 0.019465961 0.712193606 0.031655999 0.437166104
#> [49] 0.810674132 0.013460729 0.488821445 0.744846501 0.679675371 0.744846501
#> [55] 0.447569650 0.325837409 0.045647092 0.192404848 0.447569650 0.286175825
#> [61] 0.854793144 0.932615008 0.053647959 0.183434941 0.733901652 0.799593007
#> [67] 0.416505657 0.069971368 0.977395321 0.325837409 0.426791063 0.286175825
#> [73] 0.002316180 0.954995459 0.149110965 0.238208709 0.069971368 0.832697995
#> [79] 0.266601305 0.069971368 0.954995459 0.921428794 0.658166808 0.572492943
#> [85] 0.865945313 0.386474283 0.031655999 0.386474283 0.228786038 0.899143650
#> [91] 0.315683104 0.679675371 0.712193606 0.625789902 0.386474283 0.899143650
#> [97] 0.092699945 0.478294568 0.100916702 0.124758338 0.019465961 0.943788762
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 159 128 88 23 181 107 29 125 55 111 180 42 105
#> 10.55 20.35 18.37 16.92 16.46 11.18 15.45 15.65 19.34 17.45 14.82 12.43 19.75
#> 180.1 123 127 129 96 45 29.1 179 52 181.1 197 58 130
#> 14.82 13.00 3.53 23.41 14.54 17.42 15.45 18.63 10.42 16.46 21.60 19.34 16.47
#> 13 190 57 167 52.1 81 68 56 57.1 56.1 57.2 130.1 88.1
#> 14.34 20.81 14.46 15.55 10.42 14.06 20.62 12.21 14.46 12.21 14.46 16.47 18.37
#> 18 110 166 60 167.1 15 14 66 26 107.1 92 167.2 37
#> 15.21 17.56 19.98 13.15 15.55 22.68 12.89 22.13 15.77 11.18 22.92 15.55 12.52
#> 155 37.1 125.1 171 175 179.1 125.2 23.1 10 187 136 76 140
#> 13.08 12.52 15.65 16.57 21.91 18.63 15.65 16.92 10.53 9.92 21.83 19.22 12.68
#> 49 188 36 91 171.1 100 23.2 86 77 105.1 110.1 36.1 159.1
#> 12.19 16.16 21.19 5.33 16.57 16.07 16.92 23.81 7.27 19.75 17.56 21.19 10.55
#> 30 36.2 77.1 101 60.1 133 52.2 192 66.1 192.1 108 61 106
#> 17.43 21.19 7.27 9.97 13.15 14.65 10.42 16.44 22.13 16.44 18.29 10.12 16.67
#> 155.1 14.1 13.1 85 61.1 32 6 190.1 128.1 15.1 16 67 200
#> 13.08 12.89 14.34 16.44 10.12 20.90 15.64 20.81 20.35 22.68 8.71 24.00 24.00
#> 53 53.1 200.1 193 182 31 54 132 67.1 142 148 165 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 62 109 173 35 102 54.1 126 47 112 148.1 34 156
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35.1 143 176 198 163 131 173.1 198.1 132.1 198.2 191 54.2 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 95 176.1 75 72 65 12 200.2 22 196 34.1 196.1 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.1 1 62.1 98 84.1 102.1 185 98.1 193.1 196.2 162 196.3 34.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95.1 84.2 48 74 9 46 137 35.2 109.1 7.1 103 152.1 198.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112.1 65.1 173.2 160 162.1 53.2 95.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[85]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.008906224 1.051637991 0.773031693
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.488008832 0.007491996 -0.066348683
#> grade_iii, Cure model
#> 0.910581205
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 150 20.33 1 48 0 0
#> 194 22.40 1 38 0 1
#> 194.1 22.40 1 38 0 1
#> 51 18.23 1 83 0 1
#> 24 23.89 1 38 0 0
#> 52 10.42 1 52 0 1
#> 187 9.92 1 39 1 0
#> 189 10.51 1 NA 1 0
#> 89 11.44 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 59 10.16 1 NA 1 0
#> 26 15.77 1 49 0 1
#> 183 9.24 1 67 1 0
#> 171 16.57 1 41 0 1
#> 133 14.65 1 57 0 0
#> 78 23.88 1 43 0 0
#> 170 19.54 1 43 0 1
#> 129 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 110 17.56 1 65 0 1
#> 4 17.64 1 NA 0 1
#> 195 11.76 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 68 20.62 1 44 0 0
#> 107 11.18 1 54 1 0
#> 101 9.97 1 10 0 1
#> 107.1 11.18 1 54 1 0
#> 8 18.43 1 32 0 0
#> 157 15.10 1 47 0 0
#> 58 19.34 1 39 0 0
#> 169 22.41 1 46 0 0
#> 37.1 12.52 1 57 1 0
#> 134 17.81 1 47 1 0
#> 30 17.43 1 78 0 0
#> 85 16.44 1 36 0 0
#> 192 16.44 1 31 1 0
#> 97 19.14 1 65 0 1
#> 113 22.86 1 34 0 0
#> 93 10.33 1 52 0 1
#> 42 12.43 1 49 0 1
#> 61 10.12 1 36 0 1
#> 30.1 17.43 1 78 0 0
#> 153 21.33 1 55 1 0
#> 43 12.10 1 61 0 1
#> 57 14.46 1 45 0 1
#> 136 21.83 1 43 0 1
#> 106 16.67 1 49 1 0
#> 14 12.89 1 21 0 0
#> 159 10.55 1 50 0 1
#> 195.1 11.76 1 NA 1 0
#> 25 6.32 1 34 1 0
#> 114 13.68 1 NA 0 0
#> 158 20.14 1 74 1 0
#> 181 16.46 1 45 0 1
#> 78.1 23.88 1 43 0 0
#> 114.1 13.68 1 NA 0 0
#> 39 15.59 1 37 0 1
#> 164 23.60 1 76 0 1
#> 106.1 16.67 1 49 1 0
#> 40 18.00 1 28 1 0
#> 154 12.63 1 20 1 0
#> 184 17.77 1 38 0 0
#> 100 16.07 1 60 0 0
#> 110.1 17.56 1 65 0 1
#> 113.1 22.86 1 34 0 0
#> 52.1 10.42 1 52 0 1
#> 15 22.68 1 48 0 0
#> 16 8.71 1 71 0 1
#> 105 19.75 1 60 0 0
#> 37.2 12.52 1 57 1 0
#> 92 22.92 1 47 0 1
#> 189.1 10.51 1 NA 1 0
#> 184.1 17.77 1 38 0 0
#> 23 16.92 1 61 0 0
#> 96 14.54 1 33 0 1
#> 149 8.37 1 33 1 0
#> 49 12.19 1 48 1 0
#> 167 15.55 1 56 1 0
#> 195.2 11.76 1 NA 1 0
#> 13 14.34 1 54 0 1
#> 114.2 13.68 1 NA 0 0
#> 85.1 16.44 1 36 0 0
#> 10 10.53 1 34 0 0
#> 16.1 8.71 1 71 0 1
#> 134.1 17.81 1 47 1 0
#> 79 16.23 1 54 1 0
#> 154.1 12.63 1 20 1 0
#> 108 18.29 1 39 0 1
#> 15.1 22.68 1 48 0 0
#> 50 10.02 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 130 16.47 1 53 0 1
#> 127 3.53 1 62 0 1
#> 32 20.90 1 37 1 0
#> 4.1 17.64 1 NA 0 1
#> 49.1 12.19 1 48 1 0
#> 170.1 19.54 1 43 0 1
#> 108.1 18.29 1 39 0 1
#> 93.1 10.33 1 52 0 1
#> 61.1 10.12 1 36 0 1
#> 29 15.45 1 68 1 0
#> 181.1 16.46 1 45 0 1
#> 29.1 15.45 1 68 1 0
#> 58.1 19.34 1 39 0 0
#> 164.1 23.60 1 76 0 1
#> 110.2 17.56 1 65 0 1
#> 130.1 16.47 1 53 0 1
#> 97.1 19.14 1 65 0 1
#> 125 15.65 1 67 1 0
#> 188 16.16 1 46 0 1
#> 61.2 10.12 1 36 0 1
#> 15.2 22.68 1 48 0 0
#> 2 24.00 0 9 0 0
#> 165 24.00 0 47 0 0
#> 193 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 33 24.00 0 53 0 0
#> 62 24.00 0 71 0 0
#> 174 24.00 0 49 1 0
#> 109 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 65 24.00 0 57 1 0
#> 122 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 148 24.00 0 61 1 0
#> 131 24.00 0 66 0 0
#> 198 24.00 0 66 0 1
#> 193.1 24.00 0 45 0 1
#> 83 24.00 0 6 0 0
#> 3 24.00 0 31 1 0
#> 141 24.00 0 44 1 0
#> 47 24.00 0 38 0 1
#> 44 24.00 0 56 0 0
#> 147 24.00 0 76 1 0
#> 185 24.00 0 44 1 0
#> 148.1 24.00 0 61 1 0
#> 19 24.00 0 57 0 1
#> 118 24.00 0 44 1 0
#> 7 24.00 0 37 1 0
#> 64 24.00 0 43 0 0
#> 102 24.00 0 49 0 0
#> 135 24.00 0 58 1 0
#> 152 24.00 0 36 0 1
#> 104 24.00 0 50 1 0
#> 62.1 24.00 0 71 0 0
#> 95 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 82 24.00 0 34 0 0
#> 80 24.00 0 41 0 0
#> 20 24.00 0 46 1 0
#> 1 24.00 0 23 1 0
#> 173 24.00 0 19 0 1
#> 75 24.00 0 21 1 0
#> 27 24.00 0 63 1 0
#> 165.1 24.00 0 47 0 0
#> 20.1 24.00 0 46 1 0
#> 73.1 24.00 0 NA 0 1
#> 174.1 24.00 0 49 1 0
#> 172 24.00 0 41 0 0
#> 126 24.00 0 48 0 0
#> 35 24.00 0 51 0 0
#> 185.1 24.00 0 44 1 0
#> 122.1 24.00 0 66 0 0
#> 191 24.00 0 60 0 1
#> 138 24.00 0 44 1 0
#> 148.2 24.00 0 61 1 0
#> 75.1 24.00 0 21 1 0
#> 198.1 24.00 0 66 0 1
#> 3.1 24.00 0 31 1 0
#> 120 24.00 0 68 0 1
#> 53 24.00 0 32 0 1
#> 84 24.00 0 39 0 1
#> 82.1 24.00 0 34 0 0
#> 185.2 24.00 0 44 1 0
#> 27.1 24.00 0 63 1 0
#> 54 24.00 0 53 1 0
#> 176.2 24.00 0 43 0 1
#> 135.1 24.00 0 58 1 0
#> 54.1 24.00 0 53 1 0
#> 35.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 119 24.00 0 17 0 0
#> 144 24.00 0 28 0 1
#> 143 24.00 0 51 0 0
#> 82.2 24.00 0 34 0 0
#> 132 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 152.1 24.00 0 36 0 1
#> 135.2 24.00 0 58 1 0
#> 75.2 24.00 0 21 1 0
#> 160.1 24.00 0 31 1 0
#> 126.1 24.00 0 48 0 0
#> 142 24.00 0 53 0 0
#> 176.3 24.00 0 43 0 1
#> 122.2 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 115 24.00 0 NA 1 0
#> 147.1 24.00 0 76 1 0
#> 152.2 24.00 0 36 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.488 NA NA NA
#> 2 age, Cure model 0.00749 NA NA NA
#> 3 grade_ii, Cure model -0.0663 NA NA NA
#> 4 grade_iii, Cure model 0.911 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00891 NA NA NA
#> 2 grade_ii, Survival model 1.05 NA NA NA
#> 3 grade_iii, Survival model 0.773 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.488009 0.007492 -0.066349 0.910581
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254
#> Residual Deviance: 244.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.488008832 0.007491996 -0.066348683 0.910581205
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.008906224 1.051637991 0.773031693
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.261632744 0.175743027 0.175743027 0.407980971 0.004276907 0.882779039
#> [7] 0.946258847 0.791895917 0.656299053 0.954040092 0.550649524 0.729605053
#> [13] 0.017391520 0.296692196 0.072717278 0.341538896 0.469982699 0.226571132
#> [19] 0.250034282 0.850291091 0.938411628 0.850291091 0.375045283 0.720550819
#> [25] 0.318884000 0.161211702 0.791895917 0.429540284 0.499768296 0.599477943
#> [31] 0.599477943 0.352930372 0.098005133 0.898878898 0.817066412 0.914874680
#> [37] 0.499768296 0.214264917 0.842017250 0.747735055 0.201402179 0.530664731
#> [43] 0.765662822 0.866516478 0.984831966 0.273412925 0.580206518 0.017391520
#> [49] 0.684244839 0.045563952 0.530664731 0.418931234 0.774626562 0.449630890
#> [55] 0.646804918 0.469982699 0.098005133 0.882779039 0.122494901 0.961784949
#> [61] 0.284954139 0.791895917 0.085754897 0.449630890 0.520239542 0.738704240
#> [67] 0.977175010 0.825509179 0.693483734 0.756716948 0.599477943 0.874637884
#> [73] 0.961784949 0.429540284 0.627869723 0.774626562 0.386354695 0.122494901
#> [79] 0.656299053 0.560642110 0.992423144 0.238607732 0.825509179 0.296692196
#> [85] 0.386354695 0.898878898 0.914874680 0.702632648 0.580206518 0.702632648
#> [91] 0.318884000 0.045563952 0.469982699 0.560642110 0.352930372 0.674935791
#> [97] 0.637368127 0.914874680 0.122494901 0.000000000 0.000000000 0.000000000
#> [103] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 150 194 194.1 51 24 52 187 37 26 183 171 133 78
#> 20.33 22.40 22.40 18.23 23.89 10.42 9.92 12.52 15.77 9.24 16.57 14.65 23.88
#> 170 129 76 110 36 68 107 101 107.1 8 157 58 169
#> 19.54 23.41 19.22 17.56 21.19 20.62 11.18 9.97 11.18 18.43 15.10 19.34 22.41
#> 37.1 134 30 85 192 97 113 93 42 61 30.1 153 43
#> 12.52 17.81 17.43 16.44 16.44 19.14 22.86 10.33 12.43 10.12 17.43 21.33 12.10
#> 57 136 106 14 159 25 158 181 78.1 39 164 106.1 40
#> 14.46 21.83 16.67 12.89 10.55 6.32 20.14 16.46 23.88 15.59 23.60 16.67 18.00
#> 154 184 100 110.1 113.1 52.1 15 16 105 37.2 92 184.1 23
#> 12.63 17.77 16.07 17.56 22.86 10.42 22.68 8.71 19.75 12.52 22.92 17.77 16.92
#> 96 149 49 167 13 85.1 10 16.1 134.1 79 154.1 108 15.1
#> 14.54 8.37 12.19 15.55 14.34 16.44 10.53 8.71 17.81 16.23 12.63 18.29 22.68
#> 26.1 130 127 32 49.1 170.1 108.1 93.1 61.1 29 181.1 29.1 58.1
#> 15.77 16.47 3.53 20.90 12.19 19.54 18.29 10.33 10.12 15.45 16.46 15.45 19.34
#> 164.1 110.2 130.1 97.1 125 188 61.2 15.2 2 165 193 163 33
#> 23.60 17.56 16.47 19.14 15.65 16.16 10.12 22.68 24.00 24.00 24.00 24.00 24.00
#> 62 174 109 103 65 122 176 148 131 198 193.1 83 3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 141 47 44 147 185 148.1 19 118 7 64 102 135 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104 62.1 95 176.1 82 80 20 1 173 75 27 165.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 174.1 172 126 35 185.1 122.1 191 138 148.2 75.1 198.1 3.1 120
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 84 82.1 185.2 27.1 54 176.2 135.1 54.1 35.1 160 119 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 143 82.2 132 33.1 152.1 135.2 75.2 160.1 126.1 142 176.3 122.2 34
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147.1 152.2
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[86]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.004915339 0.612092898 0.408083405
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.25750923 0.02540619 0.10918901
#> grade_iii, Cure model
#> 0.79705354
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 6 15.64 1 39 0 0
#> 16 8.71 1 71 0 1
#> 127 3.53 1 62 0 1
#> 76 19.22 1 54 0 1
#> 149 8.37 1 33 1 0
#> 10 10.53 1 34 0 0
#> 171 16.57 1 41 0 1
#> 123 13.00 1 44 1 0
#> 42 12.43 1 49 0 1
#> 39 15.59 1 37 0 1
#> 184 17.77 1 38 0 0
#> 96 14.54 1 33 0 1
#> 10.1 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 181 16.46 1 45 0 1
#> 130 16.47 1 53 0 1
#> 97 19.14 1 65 0 1
#> 43 12.10 1 61 0 1
#> 15 22.68 1 48 0 0
#> 14 12.89 1 21 0 0
#> 168 23.72 1 70 0 0
#> 92 22.92 1 47 0 1
#> 58 19.34 1 39 0 0
#> 70 7.38 1 30 1 0
#> 129 23.41 1 53 1 0
#> 124 9.73 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 199 19.81 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 192 16.44 1 31 1 0
#> 23 16.92 1 61 0 0
#> 114 13.68 1 NA 0 0
#> 23.1 16.92 1 61 0 0
#> 42.1 12.43 1 49 0 1
#> 58.1 19.34 1 39 0 0
#> 157 15.10 1 47 0 0
#> 149.1 8.37 1 33 1 0
#> 30 17.43 1 78 0 0
#> 5 16.43 1 51 0 1
#> 91 5.33 1 61 0 1
#> 117 17.46 1 26 0 1
#> 24 23.89 1 38 0 0
#> 37 12.52 1 57 1 0
#> 167 15.55 1 56 1 0
#> 187 9.92 1 39 1 0
#> 24.1 23.89 1 38 0 0
#> 154 12.63 1 20 1 0
#> 140 12.68 1 59 1 0
#> 89 11.44 1 NA 0 0
#> 86 23.81 1 58 0 1
#> 86.1 23.81 1 58 0 1
#> 13 14.34 1 54 0 1
#> 77 7.27 1 67 0 1
#> 177 12.53 1 75 0 0
#> 110 17.56 1 65 0 1
#> 140.1 12.68 1 59 1 0
#> 195 11.76 1 NA 1 0
#> 50 10.02 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 13.1 14.34 1 54 0 1
#> 25 6.32 1 34 1 0
#> 70.1 7.38 1 30 1 0
#> 15.1 22.68 1 48 0 0
#> 97.1 19.14 1 65 0 1
#> 190 20.81 1 42 1 0
#> 117.1 17.46 1 26 0 1
#> 85 16.44 1 36 0 0
#> 179 18.63 1 42 0 0
#> 134 17.81 1 47 1 0
#> 52 10.42 1 52 0 1
#> 133 14.65 1 57 0 0
#> 158 20.14 1 74 1 0
#> 55 19.34 1 69 0 1
#> 129.1 23.41 1 53 1 0
#> 175 21.91 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 140.2 12.68 1 59 1 0
#> 16.1 8.71 1 71 0 1
#> 57 14.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 140.3 12.68 1 59 1 0
#> 66 22.13 1 53 0 0
#> 49 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 180 14.82 1 37 0 0
#> 169 22.41 1 46 0 0
#> 14.1 12.89 1 21 0 0
#> 50.1 10.02 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 77.1 7.27 1 67 0 1
#> 153.1 21.33 1 55 1 0
#> 153.2 21.33 1 55 1 0
#> 125.1 15.65 1 67 1 0
#> 134.1 17.81 1 47 1 0
#> 145 10.07 1 65 1 0
#> 110.1 17.56 1 65 0 1
#> 91.1 5.33 1 61 0 1
#> 192.1 16.44 1 31 1 0
#> 184.1 17.77 1 38 0 0
#> 79.2 16.23 1 54 1 0
#> 86.2 23.81 1 58 0 1
#> 136 21.83 1 43 0 1
#> 39.1 15.59 1 37 0 1
#> 29 15.45 1 68 1 0
#> 32 20.90 1 37 1 0
#> 158.1 20.14 1 74 1 0
#> 134.2 17.81 1 47 1 0
#> 114.1 13.68 1 NA 0 0
#> 189.1 10.51 1 NA 1 0
#> 13.2 14.34 1 54 0 1
#> 149.2 8.37 1 33 1 0
#> 11 24.00 0 42 0 1
#> 141 24.00 0 44 1 0
#> 152 24.00 0 36 0 1
#> 21 24.00 0 47 0 0
#> 1 24.00 0 23 1 0
#> 182 24.00 0 35 0 0
#> 147 24.00 0 76 1 0
#> 152.1 24.00 0 36 0 1
#> 83 24.00 0 6 0 0
#> 174 24.00 0 49 1 0
#> 193 24.00 0 45 0 1
#> 2 24.00 0 9 0 0
#> 109 24.00 0 48 0 0
#> 73 24.00 0 NA 0 1
#> 147.1 24.00 0 76 1 0
#> 162 24.00 0 51 0 0
#> 126 24.00 0 48 0 0
#> 67 24.00 0 25 0 0
#> 146 24.00 0 63 1 0
#> 147.2 24.00 0 76 1 0
#> 80 24.00 0 41 0 0
#> 62 24.00 0 71 0 0
#> 87 24.00 0 27 0 0
#> 160 24.00 0 31 1 0
#> 141.1 24.00 0 44 1 0
#> 152.2 24.00 0 36 0 1
#> 44 24.00 0 56 0 0
#> 156 24.00 0 50 1 0
#> 21.1 24.00 0 47 0 0
#> 191 24.00 0 60 0 1
#> 156.1 24.00 0 50 1 0
#> 71 24.00 0 51 0 0
#> 138 24.00 0 44 1 0
#> 48 24.00 0 31 1 0
#> 115 24.00 0 NA 1 0
#> 102 24.00 0 49 0 0
#> 27 24.00 0 63 1 0
#> 7 24.00 0 37 1 0
#> 33 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 7.1 24.00 0 37 1 0
#> 104 24.00 0 50 1 0
#> 7.2 24.00 0 37 1 0
#> 73.1 24.00 0 NA 0 1
#> 160.1 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 27.1 24.00 0 63 1 0
#> 102.1 24.00 0 49 0 0
#> 7.3 24.00 0 37 1 0
#> 116 24.00 0 58 0 1
#> 74 24.00 0 43 0 1
#> 141.2 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 119 24.00 0 17 0 0
#> 7.4 24.00 0 37 1 0
#> 3 24.00 0 31 1 0
#> 67.1 24.00 0 25 0 0
#> 147.3 24.00 0 76 1 0
#> 2.1 24.00 0 9 0 0
#> 67.2 24.00 0 25 0 0
#> 186 24.00 0 45 1 0
#> 186.1 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 120 24.00 0 68 0 1
#> 72 24.00 0 40 0 1
#> 83.1 24.00 0 6 0 0
#> 193.1 24.00 0 45 0 1
#> 174.1 24.00 0 49 1 0
#> 9 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 112 24.00 0 61 0 0
#> 109.1 24.00 0 48 0 0
#> 144 24.00 0 28 0 1
#> 138.1 24.00 0 44 1 0
#> 31 24.00 0 36 0 1
#> 137 24.00 0 45 1 0
#> 82 24.00 0 34 0 0
#> 182.1 24.00 0 35 0 0
#> 73.2 24.00 0 NA 0 1
#> 2.2 24.00 0 9 0 0
#> 35 24.00 0 51 0 0
#> 126.1 24.00 0 48 0 0
#> 198 24.00 0 66 0 1
#> 9.1 24.00 0 31 1 0
#> 71.1 24.00 0 51 0 0
#> 28 24.00 0 67 1 0
#> 196 24.00 0 19 0 0
#> 104.1 24.00 0 50 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.26 NA NA NA
#> 2 age, Cure model 0.0254 NA NA NA
#> 3 grade_ii, Cure model 0.109 NA NA NA
#> 4 grade_iii, Cure model 0.797 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00492 NA NA NA
#> 2 grade_ii, Survival model 0.612 NA NA NA
#> 3 grade_iii, Survival model 0.408 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.25751 0.02541 0.10919 0.79705
#>
#> Degrees of Freedom: 184 Total (i.e. Null); 181 Residual
#> Null Deviance: 254.9
#> Residual Deviance: 242 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.25750923 0.02540619 0.10918901 0.79705354
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.004915339 0.612092898 0.408083405
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.59444527 0.89043371 0.99164320 0.30976030 0.90768741 0.83800519
#> [7] 0.48011178 0.71392827 0.80289929 0.60380818 0.38061979 0.66839215
#> [13] 0.83800519 0.57591744 0.49998999 0.49006691 0.32025906 0.82923452
#> [19] 0.13324414 0.72301935 0.07337527 0.12179174 0.27916604 0.93303601
#> [25] 0.08728471 0.20465321 0.54806007 0.50987277 0.45012747 0.45012747
#> [31] 0.80289929 0.27916604 0.64066672 0.90768741 0.44013948 0.53840559
#> [37] 0.97498482 0.42053027 0.01213851 0.79403836 0.62224484 0.87304702
#> [43] 0.01213851 0.77626933 0.74113163 0.04051809 0.04051809 0.68683545
#> [49] 0.94983180 0.78513834 0.40062096 0.74113163 0.54806007 0.68683545
#> [55] 0.96660331 0.93303601 0.13324414 0.32025906 0.24784739 0.42053027
#> [61] 0.50987277 0.34079026 0.35127516 0.85551086 0.65912191 0.25859272
#> [67] 0.27916604 0.08728471 0.18013049 0.74113163 0.89043371 0.67762669
#> [73] 0.11012787 0.88175437 0.74113163 0.16794379 0.82045322 0.64988342
#> [79] 0.15595686 0.72301935 0.47010908 0.94983180 0.20465321 0.20465321
#> [85] 0.57591744 0.35127516 0.86429406 0.40062096 0.97498482 0.50987277
#> [91] 0.38061979 0.54806007 0.04051809 0.19247659 0.60380818 0.63147729
#> [97] 0.23686396 0.25859272 0.35127516 0.68683545 0.90768741 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 6 16 127 76 149 10 171 123 42 39 184 96 10.1
#> 15.64 8.71 3.53 19.22 8.37 10.53 16.57 13.00 12.43 15.59 17.77 14.54 10.53
#> 125 181 130 97 43 15 14 168 92 58 70 129 153
#> 15.65 16.46 16.47 19.14 12.10 22.68 12.89 23.72 22.92 19.34 7.38 23.41 21.33
#> 79 192 23 23.1 42.1 58.1 157 149.1 30 5 91 117 24
#> 16.23 16.44 16.92 16.92 12.43 19.34 15.10 8.37 17.43 16.43 5.33 17.46 23.89
#> 37 167 187 24.1 154 140 86 86.1 13 77 177 110 140.1
#> 12.52 15.55 9.92 23.89 12.63 12.68 23.81 23.81 14.34 7.27 12.53 17.56 12.68
#> 79.1 13.1 25 70.1 15.1 97.1 190 117.1 85 179 134 52 133
#> 16.23 14.34 6.32 7.38 22.68 19.14 20.81 17.46 16.44 18.63 17.81 10.42 14.65
#> 158 55 129.1 175 140.2 16.1 57 69 183 140.3 66 49 180
#> 20.14 19.34 23.41 21.91 12.68 8.71 14.46 23.23 9.24 12.68 22.13 12.19 14.82
#> 169 14.1 106 77.1 153.1 153.2 125.1 134.1 145 110.1 91.1 192.1 184.1
#> 22.41 12.89 16.67 7.27 21.33 21.33 15.65 17.81 10.07 17.56 5.33 16.44 17.77
#> 79.2 86.2 136 39.1 29 32 158.1 134.2 13.2 149.2 11 141 152
#> 16.23 23.81 21.83 15.59 15.45 20.90 20.14 17.81 14.34 8.37 24.00 24.00 24.00
#> 21 1 182 147 152.1 83 174 193 2 109 147.1 162 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 67 146 147.2 80 62 87 160 141.1 152.2 44 156 21.1 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.1 71 138 48 102 27 7 33 103 7.1 104 7.2 160.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151 27.1 102.1 7.3 116 74 141.2 95 119 7.4 3 67.1 147.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 2.1 67.2 186 186.1 17 120 72 83.1 193.1 174.1 9 98 112
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 109.1 144 138.1 31 137 82 182.1 2.2 35 126.1 198 9.1 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 196 104.1
#> 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[87]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.005833565 0.222157399 0.079972352
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.678636468 0.008594507 0.498396155
#> grade_iii, Cure model
#> 1.009429425
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 24 23.89 1 38 0 0
#> 136 21.83 1 43 0 1
#> 167 15.55 1 56 1 0
#> 155 13.08 1 26 0 0
#> 153 21.33 1 55 1 0
#> 25 6.32 1 34 1 0
#> 140 12.68 1 59 1 0
#> 110 17.56 1 65 0 1
#> 32 20.90 1 37 1 0
#> 61 10.12 1 36 0 1
#> 101 9.97 1 10 0 1
#> 92 22.92 1 47 0 1
#> 60 13.15 1 38 1 0
#> 36 21.19 1 48 0 1
#> 158 20.14 1 74 1 0
#> 181 16.46 1 45 0 1
#> 199 19.81 1 NA 0 1
#> 183 9.24 1 67 1 0
#> 50 10.02 1 NA 1 0
#> 66 22.13 1 53 0 0
#> 106 16.67 1 49 1 0
#> 57 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 43 12.10 1 61 0 1
#> 181.1 16.46 1 45 0 1
#> 153.1 21.33 1 55 1 0
#> 61.1 10.12 1 36 0 1
#> 199.1 19.81 1 NA 0 1
#> 15 22.68 1 48 0 0
#> 123.1 13.00 1 44 1 0
#> 41 18.02 1 40 1 0
#> 105 19.75 1 60 0 0
#> 41.1 18.02 1 40 1 0
#> 10 10.53 1 34 0 0
#> 125 15.65 1 67 1 0
#> 26 15.77 1 49 0 1
#> 130 16.47 1 53 0 1
#> 70 7.38 1 30 1 0
#> 10.1 10.53 1 34 0 0
#> 32.1 20.90 1 37 1 0
#> 177 12.53 1 75 0 0
#> 197 21.60 1 69 1 0
#> 177.1 12.53 1 75 0 0
#> 97 19.14 1 65 0 1
#> 16 8.71 1 71 0 1
#> 99 21.19 1 38 0 1
#> 192 16.44 1 31 1 0
#> 199.2 19.81 1 NA 0 1
#> 8 18.43 1 32 0 0
#> 37 12.52 1 57 1 0
#> 150 20.33 1 48 0 0
#> 18 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 190 20.81 1 42 1 0
#> 157 15.10 1 47 0 0
#> 68.1 20.62 1 44 0 0
#> 30 17.43 1 78 0 0
#> 153.2 21.33 1 55 1 0
#> 56 12.21 1 60 0 0
#> 41.2 18.02 1 40 1 0
#> 108 18.29 1 39 0 1
#> 194 22.40 1 38 0 1
#> 86 23.81 1 58 0 1
#> 10.2 10.53 1 34 0 0
#> 108.1 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 10.3 10.53 1 34 0 0
#> 149 8.37 1 33 1 0
#> 15.1 22.68 1 48 0 0
#> 179 18.63 1 42 0 0
#> 57.1 14.46 1 45 0 1
#> 179.1 18.63 1 42 0 0
#> 159 10.55 1 50 0 1
#> 128 20.35 1 35 0 1
#> 145 10.07 1 65 1 0
#> 188 16.16 1 46 0 1
#> 63 22.77 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 4 17.64 1 NA 0 1
#> 8.1 18.43 1 32 0 0
#> 168 23.72 1 70 0 0
#> 136.1 21.83 1 43 0 1
#> 127 3.53 1 62 0 1
#> 134 17.81 1 47 1 0
#> 69 23.23 1 25 0 1
#> 99.1 21.19 1 38 0 1
#> 155.1 13.08 1 26 0 0
#> 133 14.65 1 57 0 0
#> 56.1 12.21 1 60 0 0
#> 49 12.19 1 48 1 0
#> 5 16.43 1 51 0 1
#> 129.1 23.41 1 53 1 0
#> 50.1 10.02 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 130.1 16.47 1 53 0 1
#> 49.1 12.19 1 48 1 0
#> 32.2 20.90 1 37 1 0
#> 195 11.76 1 NA 1 0
#> 52.1 10.42 1 52 0 1
#> 99.2 21.19 1 38 0 1
#> 92.1 22.92 1 47 0 1
#> 154 12.63 1 20 1 0
#> 108.2 18.29 1 39 0 1
#> 89 11.44 1 NA 0 0
#> 81 14.06 1 34 0 0
#> 6 15.64 1 39 0 0
#> 117 17.46 1 26 0 1
#> 60.1 13.15 1 38 1 0
#> 184 17.77 1 38 0 0
#> 168.1 23.72 1 70 0 0
#> 77 7.27 1 67 0 1
#> 4.1 17.64 1 NA 0 1
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 116 24.00 0 58 0 1
#> 156 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 116.1 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 80 24.00 0 41 0 0
#> 83 24.00 0 6 0 0
#> 74 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 47 24.00 0 38 0 1
#> 144.1 24.00 0 28 0 1
#> 162 24.00 0 51 0 0
#> 38 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 22 24.00 0 52 1 0
#> 163 24.00 0 66 0 0
#> 142 24.00 0 53 0 0
#> 103 24.00 0 56 1 0
#> 172 24.00 0 41 0 0
#> 72 24.00 0 40 0 1
#> 27 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 33 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 71 24.00 0 51 0 0
#> 116.2 24.00 0 58 0 1
#> 62 24.00 0 71 0 0
#> 156.1 24.00 0 50 1 0
#> 196.1 24.00 0 19 0 0
#> 83.1 24.00 0 6 0 0
#> 196.2 24.00 0 19 0 0
#> 118 24.00 0 44 1 0
#> 62.1 24.00 0 71 0 0
#> 135 24.00 0 58 1 0
#> 162.1 24.00 0 51 0 0
#> 160 24.00 0 31 1 0
#> 20 24.00 0 46 1 0
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 144.2 24.00 0 28 0 1
#> 84.1 24.00 0 39 0 1
#> 182 24.00 0 35 0 0
#> 160.1 24.00 0 31 1 0
#> 38.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 95.1 24.00 0 68 0 1
#> 143 24.00 0 51 0 0
#> 12 24.00 0 63 0 0
#> 7 24.00 0 37 1 0
#> 162.2 24.00 0 51 0 0
#> 2 24.00 0 9 0 0
#> 161 24.00 0 45 0 0
#> 148 24.00 0 61 1 0
#> 62.2 24.00 0 71 0 0
#> 142.1 24.00 0 53 0 0
#> 200 24.00 0 64 0 0
#> 20.1 24.00 0 46 1 0
#> 161.1 24.00 0 45 0 0
#> 135.1 24.00 0 58 1 0
#> 72.1 24.00 0 40 0 1
#> 95.2 24.00 0 68 0 1
#> 2.1 24.00 0 9 0 0
#> 137.1 24.00 0 45 1 0
#> 141.1 24.00 0 44 1 0
#> 186 24.00 0 45 1 0
#> 122 24.00 0 66 0 0
#> 186.1 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 132 24.00 0 55 0 0
#> 28.1 24.00 0 67 1 0
#> 83.2 24.00 0 6 0 0
#> 83.3 24.00 0 6 0 0
#> 172.1 24.00 0 41 0 0
#> 151 24.00 0 42 0 0
#> 44 24.00 0 56 0 0
#> 176 24.00 0 43 0 1
#> 142.2 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 62.3 24.00 0 71 0 0
#> 126 24.00 0 48 0 0
#> 80.1 24.00 0 41 0 0
#> 163.1 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 182.1 24.00 0 35 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.679 NA NA NA
#> 2 age, Cure model 0.00859 NA NA NA
#> 3 grade_ii, Cure model 0.498 NA NA NA
#> 4 grade_iii, Cure model 1.01 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00583 NA NA NA
#> 2 grade_ii, Survival model 0.222 NA NA NA
#> 3 grade_iii, Survival model 0.0800 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.678636 0.008595 0.498396 1.009429
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 253.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.678636468 0.008594507 0.498396155 1.009429425
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.005833565 0.222157399 0.079972352
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.001980361 0.102527761 0.554888724 0.649559031 0.128194179 0.977419291
#> [7] 0.691961789 0.402384257 0.187106958 0.876579201 0.909989039 0.047204387
#> [13] 0.628465937 0.153397935 0.258477545 0.462650070 0.921182455 0.093971263
#> [19] 0.432421898 0.596803538 0.670749014 0.788988341 0.462650070 0.128194179
#> [25] 0.876579201 0.069917890 0.670749014 0.353830347 0.267831495 0.353830347
#> [31] 0.810941012 0.534100762 0.523758160 0.442512623 0.954899035 0.810941012
#> [37] 0.187106958 0.713359568 0.119354401 0.713359568 0.277282953 0.932397024
#> [43] 0.153397935 0.482934949 0.305843199 0.734805122 0.249187177 0.565322334
#> [49] 0.221999910 0.212988817 0.575767844 0.221999910 0.422345691 0.128194179
#> [55] 0.745623919 0.353830347 0.325071918 0.085617439 0.006899477 0.810941012
#> [61] 0.325071918 0.025943668 0.810941012 0.943650047 0.069917890 0.286818484
#> [67] 0.596803538 0.286818484 0.799950308 0.239980668 0.898792614 0.513453424
#> [73] 0.062036859 0.482934949 0.305843199 0.013026412 0.102527761 0.988693819
#> [79] 0.382616077 0.039575059 0.153397935 0.649559031 0.586259000 0.745623919
#> [85] 0.767288890 0.503184080 0.025943668 0.854434242 0.442512623 0.767288890
#> [91] 0.187106958 0.854434242 0.153397935 0.047204387 0.702669738 0.325071918
#> [97] 0.617829241 0.544474553 0.412356611 0.628465937 0.392475416 0.013026412
#> [103] 0.966141630 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 24 136 167 155 153 25 140 110 32 61 101 92 60
#> 23.89 21.83 15.55 13.08 21.33 6.32 12.68 17.56 20.90 10.12 9.97 22.92 13.15
#> 36 158 181 183 66 106 57 123 43 181.1 153.1 61.1 15
#> 21.19 20.14 16.46 9.24 22.13 16.67 14.46 13.00 12.10 16.46 21.33 10.12 22.68
#> 123.1 41 105 41.1 10 125 26 130 70 10.1 32.1 177 197
#> 13.00 18.02 19.75 18.02 10.53 15.65 15.77 16.47 7.38 10.53 20.90 12.53 21.60
#> 177.1 97 16 99 192 8 37 150 18 68 190 157 68.1
#> 12.53 19.14 8.71 21.19 16.44 18.43 12.52 20.33 15.21 20.62 20.81 15.10 20.62
#> 30 153.2 56 41.2 108 194 86 10.2 108.1 129 10.3 149 15.1
#> 17.43 21.33 12.21 18.02 18.29 22.40 23.81 10.53 18.29 23.41 10.53 8.37 22.68
#> 179 57.1 179.1 159 128 145 188 63 192.1 8.1 168 136.1 127
#> 18.63 14.46 18.63 10.55 20.35 10.07 16.16 22.77 16.44 18.43 23.72 21.83 3.53
#> 134 69 99.1 155.1 133 56.1 49 5 129.1 52 130.1 49.1 32.2
#> 17.81 23.23 21.19 13.08 14.65 12.21 12.19 16.43 23.41 10.42 16.47 12.19 20.90
#> 52.1 99.2 92.1 154 108.2 81 6 117 60.1 184 168.1 77 165
#> 10.42 21.19 22.92 12.63 18.29 14.06 15.64 17.46 13.15 17.77 23.72 7.27 24.00
#> 144 116 156 3 193 196 116.1 138 80 83 74 84 47
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144.1 162 38 137 22 163 142 103 172 72 27 98 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 71 116.2 62 156.1 196.1 83.1 196.2 118 62.1 135 162.1 160
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 20 173 141 144.2 84.1 182 160.1 38.1 28 95.1 143 12 7
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 162.2 2 161 148 62.2 142.1 200 20.1 161.1 135.1 72.1 95.2 2.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 141.1 186 122 186.1 75 132 28.1 83.2 83.3 172.1 151 44
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 142.2 62.3 126 80.1 163.1 54 182.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[88]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01358037 0.05238906 -0.05744450
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.172706396 -0.002368446 -0.276291052
#> grade_iii, Cure model
#> 0.794192893
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 125 15.65 1 67 1 0
#> 149 8.37 1 33 1 0
#> 190 20.81 1 42 1 0
#> 56 12.21 1 60 0 0
#> 188 16.16 1 46 0 1
#> 25 6.32 1 34 1 0
#> 123 13.00 1 44 1 0
#> 56.1 12.21 1 60 0 0
#> 96 14.54 1 33 0 1
#> 78 23.88 1 43 0 0
#> 127 3.53 1 62 0 1
#> 18 15.21 1 49 1 0
#> 41 18.02 1 40 1 0
#> 129 23.41 1 53 1 0
#> 192 16.44 1 31 1 0
#> 10 10.53 1 34 0 0
#> 61 10.12 1 36 0 1
#> 106 16.67 1 49 1 0
#> 90 20.94 1 50 0 1
#> 111 17.45 1 47 0 1
#> 86 23.81 1 58 0 1
#> 170 19.54 1 43 0 1
#> 56.2 12.21 1 60 0 0
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 42 12.43 1 49 0 1
#> 117 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 114 13.68 1 NA 0 0
#> 37 12.52 1 57 1 0
#> 15 22.68 1 48 0 0
#> 91 5.33 1 61 0 1
#> 86.1 23.81 1 58 0 1
#> 56.3 12.21 1 60 0 0
#> 55 19.34 1 69 0 1
#> 154 12.63 1 20 1 0
#> 108 18.29 1 39 0 1
#> 123.1 13.00 1 44 1 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 128 20.35 1 35 0 1
#> 45 17.42 1 54 0 1
#> 101 9.97 1 10 0 1
#> 68 20.62 1 44 0 0
#> 81 14.06 1 34 0 0
#> 106.1 16.67 1 49 1 0
#> 52 10.42 1 52 0 1
#> 4 17.64 1 NA 0 1
#> 25.1 6.32 1 34 1 0
#> 88 18.37 1 47 0 0
#> 41.1 18.02 1 40 1 0
#> 188.1 16.16 1 46 0 1
#> 155 13.08 1 26 0 0
#> 16 8.71 1 71 0 1
#> 153.1 21.33 1 55 1 0
#> 101.1 9.97 1 10 0 1
#> 133 14.65 1 57 0 0
#> 101.2 9.97 1 10 0 1
#> 155.1 13.08 1 26 0 0
#> 37.1 12.52 1 57 1 0
#> 45.1 17.42 1 54 0 1
#> 100 16.07 1 60 0 0
#> 88.1 18.37 1 47 0 0
#> 91.1 5.33 1 61 0 1
#> 81.1 14.06 1 34 0 0
#> 16.1 8.71 1 71 0 1
#> 117.1 17.46 1 26 0 1
#> 199 19.81 1 NA 0 1
#> 50 10.02 1 NA 1 0
#> 155.2 13.08 1 26 0 0
#> 155.3 13.08 1 26 0 0
#> 37.2 12.52 1 57 1 0
#> 25.2 6.32 1 34 1 0
#> 36 21.19 1 48 0 1
#> 70 7.38 1 30 1 0
#> 129.1 23.41 1 53 1 0
#> 100.1 16.07 1 60 0 0
#> 32 20.90 1 37 1 0
#> 190.1 20.81 1 42 1 0
#> 63 22.77 1 31 1 0
#> 184 17.77 1 38 0 0
#> 77 7.27 1 67 0 1
#> 15.1 22.68 1 48 0 0
#> 164 23.60 1 76 0 1
#> 58 19.34 1 39 0 0
#> 157 15.10 1 47 0 0
#> 164.1 23.60 1 76 0 1
#> 184.1 17.77 1 38 0 0
#> 5 16.43 1 51 0 1
#> 153.2 21.33 1 55 1 0
#> 180 14.82 1 37 0 0
#> 101.3 9.97 1 10 0 1
#> 4.1 17.64 1 NA 0 1
#> 90.1 20.94 1 50 0 1
#> 183 9.24 1 67 1 0
#> 14 12.89 1 21 0 0
#> 183.1 9.24 1 67 1 0
#> 16.2 8.71 1 71 0 1
#> 76.1 19.22 1 54 0 1
#> 37.3 12.52 1 57 1 0
#> 39 15.59 1 37 0 1
#> 56.4 12.21 1 60 0 0
#> 177 12.53 1 75 0 0
#> 133.1 14.65 1 57 0 0
#> 189 10.51 1 NA 1 0
#> 55.1 19.34 1 69 0 1
#> 69 23.23 1 25 0 1
#> 184.2 17.77 1 38 0 0
#> 149.1 8.37 1 33 1 0
#> 110 17.56 1 65 0 1
#> 149.2 8.37 1 33 1 0
#> 4.2 17.64 1 NA 0 1
#> 27 24.00 0 63 1 0
#> 174 24.00 0 49 1 0
#> 98 24.00 0 34 1 0
#> 122 24.00 0 66 0 0
#> 200 24.00 0 64 0 0
#> 27.1 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 54 24.00 0 53 1 0
#> 31 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 47 24.00 0 38 0 1
#> 148.1 24.00 0 61 1 0
#> 20 24.00 0 46 1 0
#> 34 24.00 0 36 0 0
#> 152 24.00 0 36 0 1
#> 84 24.00 0 39 0 1
#> 12 24.00 0 63 0 0
#> 152.1 24.00 0 36 0 1
#> 173 24.00 0 19 0 1
#> 141 24.00 0 44 1 0
#> 11 24.00 0 42 0 1
#> 31.1 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 94 24.00 0 51 0 1
#> 31.2 24.00 0 36 0 1
#> 146 24.00 0 63 1 0
#> 95 24.00 0 68 0 1
#> 200.1 24.00 0 64 0 0
#> 156 24.00 0 50 1 0
#> 62 24.00 0 71 0 0
#> 83.1 24.00 0 6 0 0
#> 38 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 22 24.00 0 52 1 0
#> 131 24.00 0 66 0 0
#> 21 24.00 0 47 0 0
#> 64 24.00 0 43 0 0
#> 17 24.00 0 38 0 1
#> 143.1 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 38.2 24.00 0 31 1 0
#> 22.1 24.00 0 52 1 0
#> 95.1 24.00 0 68 0 1
#> 98.1 24.00 0 34 1 0
#> 118 24.00 0 44 1 0
#> 121 24.00 0 57 1 0
#> 151 24.00 0 42 0 0
#> 137 24.00 0 45 1 0
#> 135 24.00 0 58 1 0
#> 146.2 24.00 0 63 1 0
#> 47.1 24.00 0 38 0 1
#> 151.1 24.00 0 42 0 0
#> 104 24.00 0 50 1 0
#> 104.1 24.00 0 50 1 0
#> 38.3 24.00 0 31 1 0
#> 67 24.00 0 25 0 0
#> 132 24.00 0 55 0 0
#> 112 24.00 0 61 0 0
#> 22.2 24.00 0 52 1 0
#> 104.2 24.00 0 50 1 0
#> 28 24.00 0 67 1 0
#> 109 24.00 0 48 0 0
#> 151.2 24.00 0 42 0 0
#> 137.1 24.00 0 45 1 0
#> 146.3 24.00 0 63 1 0
#> 172.1 24.00 0 41 0 0
#> 135.1 24.00 0 58 1 0
#> 109.1 24.00 0 48 0 0
#> 156.1 24.00 0 50 1 0
#> 87 24.00 0 27 0 0
#> 67.1 24.00 0 25 0 0
#> 38.4 24.00 0 31 1 0
#> 28.1 24.00 0 67 1 0
#> 156.2 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 116 24.00 0 58 0 1
#> 34.1 24.00 0 36 0 0
#> 191 24.00 0 60 0 1
#> 131.1 24.00 0 66 0 0
#> 71 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 80 24.00 0 41 0 0
#> 178 24.00 0 52 1 0
#> 72 24.00 0 40 0 1
#> 148.2 24.00 0 61 1 0
#> 7 24.00 0 37 1 0
#> 122.1 24.00 0 66 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.173 NA NA NA
#> 2 age, Cure model -0.00237 NA NA NA
#> 3 grade_ii, Cure model -0.276 NA NA NA
#> 4 grade_iii, Cure model 0.794 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0136 NA NA NA
#> 2 grade_ii, Survival model 0.0524 NA NA NA
#> 3 grade_iii, Survival model -0.0574 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.172706 -0.002368 -0.276291 0.794193
#>
#> Degrees of Freedom: 192 Total (i.e. Null); 189 Residual
#> Null Deviance: 266.1
#> Residual Deviance: 257 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.172706396 -0.002368446 -0.276291052 0.794192893
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01358037 0.05238906 -0.05744450
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 2.835714e-01 8.172849e-01 3.706445e-02 5.677095e-01 2.446767e-01
#> [6] 8.984280e-01 4.402240e-01 5.677095e-01 3.590959e-01 5.248689e-05
#> [11] 9.825404e-01 3.043592e-01 1.233201e-01 3.369747e-03 2.261701e-01
#> [16] 6.367803e-01 6.661130e-01 2.084429e-01 2.622476e-02 1.830663e-01
#> [21] 3.153494e-04 6.356779e-02 5.677095e-01 9.688553e-02 5.862051e-02
#> [26] 5.541398e-01 1.671678e-01 5.386554e-02 5.024501e-01 1.042292e-02
#> [31] 9.482893e-01 3.153494e-04 5.677095e-01 6.870445e-02 4.771587e-01
#> [36] 1.163869e-01 4.402240e-01 1.497242e-02 8.486986e-02 4.935523e-02
#> [41] 1.913813e-01 6.810064e-01 4.500911e-02 3.705825e-01 2.084429e-01
#> [46] 6.513585e-01 8.984280e-01 1.032700e-01 1.233201e-01 2.446767e-01
#> [51] 3.937222e-01 7.701012e-01 1.497242e-02 6.810064e-01 3.367691e-01
#> [56] 6.810064e-01 3.937222e-01 5.024501e-01 1.913813e-01 2.637245e-01
#> [61] 1.032700e-01 9.482893e-01 3.705825e-01 7.701012e-01 1.671678e-01
#> [66] 3.937222e-01 3.937222e-01 5.024501e-01 8.984280e-01 2.295597e-02
#> [71] 8.653766e-01 3.369747e-03 2.637245e-01 3.321000e-02 3.706445e-02
#> [76] 8.337590e-03 1.373942e-01 8.818063e-01 1.042292e-02 1.293880e-03
#> [81] 6.870445e-02 3.149997e-01 1.293880e-03 1.373942e-01 2.353274e-01
#> [86] 1.497242e-02 3.258126e-01 6.810064e-01 2.622476e-02 7.395270e-01
#> [91] 4.646819e-01 7.395270e-01 7.701012e-01 8.486986e-02 5.024501e-01
#> [96] 2.938865e-01 5.677095e-01 4.897001e-01 3.367691e-01 6.870445e-02
#> [101] 6.403068e-03 1.373942e-01 8.172849e-01 1.592793e-01 8.172849e-01
#> [106] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [111] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [116] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [121] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [126] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [131] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [136] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [141] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [146] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [151] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [156] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [161] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [166] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [171] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [176] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [181] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [186] 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00
#> [191] 0.000000e+00 0.000000e+00 0.000000e+00
#>
#> $Time
#> 125 149 190 56 188 25 123 56.1 96 78 127 18 41
#> 15.65 8.37 20.81 12.21 16.16 6.32 13.00 12.21 14.54 23.88 3.53 15.21 18.02
#> 129 192 10 61 106 90 111 86 170 56.2 179 166 42
#> 23.41 16.44 10.53 10.12 16.67 20.94 17.45 23.81 19.54 12.21 18.63 19.98 12.43
#> 117 158 37 15 91 86.1 56.3 55 154 108 123.1 153 76
#> 17.46 20.14 12.52 22.68 5.33 23.81 12.21 19.34 12.63 18.29 13.00 21.33 19.22
#> 128 45 101 68 81 106.1 52 25.1 88 41.1 188.1 155 16
#> 20.35 17.42 9.97 20.62 14.06 16.67 10.42 6.32 18.37 18.02 16.16 13.08 8.71
#> 153.1 101.1 133 101.2 155.1 37.1 45.1 100 88.1 91.1 81.1 16.1 117.1
#> 21.33 9.97 14.65 9.97 13.08 12.52 17.42 16.07 18.37 5.33 14.06 8.71 17.46
#> 155.2 155.3 37.2 25.2 36 70 129.1 100.1 32 190.1 63 184 77
#> 13.08 13.08 12.52 6.32 21.19 7.38 23.41 16.07 20.90 20.81 22.77 17.77 7.27
#> 15.1 164 58 157 164.1 184.1 5 153.2 180 101.3 90.1 183 14
#> 22.68 23.60 19.34 15.10 23.60 17.77 16.43 21.33 14.82 9.97 20.94 9.24 12.89
#> 183.1 16.2 76.1 37.3 39 56.4 177 133.1 55.1 69 184.2 149.1 110
#> 9.24 8.71 19.22 12.52 15.59 12.21 12.53 14.65 19.34 23.23 17.77 8.37 17.56
#> 149.2 27 174 98 122 200 27.1 148 54 31 143 83 47
#> 8.37 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 20 34 152 84 12 152.1 173 141 11 31.1 172 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31.2 146 95 200.1 156 62 83.1 38 146.1 22 131 21 64
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 143.1 38.1 38.2 22.1 95.1 98.1 118 121 151 137 135 146.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 47.1 151.1 104 104.1 38.3 67 132 112 22.2 104.2 28 109 151.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 137.1 146.3 172.1 135.1 109.1 156.1 87 67.1 38.4 28.1 156.2 3 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 34.1 191 131.1 71 3.1 80 178 72 148.2 7 122.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[89]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003850403 0.884318249 0.277342271
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.97821651 0.01451977 0.30921445
#> grade_iii, Cure model
#> 1.42337200
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 133 14.65 1 57 0 0
#> 86 23.81 1 58 0 1
#> 188 16.16 1 46 0 1
#> 190 20.81 1 42 1 0
#> 145 10.07 1 65 1 0
#> 111 17.45 1 47 0 1
#> 52 10.42 1 52 0 1
#> 26 15.77 1 49 0 1
#> 26.1 15.77 1 49 0 1
#> 181 16.46 1 45 0 1
#> 8 18.43 1 32 0 0
#> 32 20.90 1 37 1 0
#> 25 6.32 1 34 1 0
#> 13 14.34 1 54 0 1
#> 8.1 18.43 1 32 0 0
#> 91 5.33 1 61 0 1
#> 90 20.94 1 50 0 1
#> 49 12.19 1 48 1 0
#> 189 10.51 1 NA 1 0
#> 36 21.19 1 48 0 1
#> 164 23.60 1 76 0 1
#> 128 20.35 1 35 0 1
#> 59 10.16 1 NA 1 0
#> 189.1 10.51 1 NA 1 0
#> 153 21.33 1 55 1 0
#> 183 9.24 1 67 1 0
#> 187 9.92 1 39 1 0
#> 192 16.44 1 31 1 0
#> 88 18.37 1 47 0 0
#> 125 15.65 1 67 1 0
#> 88.1 18.37 1 47 0 0
#> 125.1 15.65 1 67 1 0
#> 77 7.27 1 67 0 1
#> 18 15.21 1 49 1 0
#> 85 16.44 1 36 0 0
#> 106 16.67 1 49 1 0
#> 99 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 139 21.49 1 63 1 0
#> 192.1 16.44 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 155 13.08 1 26 0 0
#> 187.1 9.92 1 39 1 0
#> 167 15.55 1 56 1 0
#> 197 21.60 1 69 1 0
#> 77.1 7.27 1 67 0 1
#> 43 12.10 1 61 0 1
#> 55 19.34 1 69 0 1
#> 26.2 15.77 1 49 0 1
#> 166 19.98 1 48 0 0
#> 41 18.02 1 40 1 0
#> 107 11.18 1 54 1 0
#> 166.1 19.98 1 48 0 0
#> 26.3 15.77 1 49 0 1
#> 29 15.45 1 68 1 0
#> 68 20.62 1 44 0 0
#> 124 9.73 1 NA 1 0
#> 78 23.88 1 43 0 0
#> 90.1 20.94 1 50 0 1
#> 145.1 10.07 1 65 1 0
#> 113 22.86 1 34 0 0
#> 183.1 9.24 1 67 1 0
#> 51 18.23 1 83 0 1
#> 111.1 17.45 1 47 0 1
#> 107.1 11.18 1 54 1 0
#> 41.1 18.02 1 40 1 0
#> 189.2 10.51 1 NA 1 0
#> 15 22.68 1 48 0 0
#> 183.2 9.24 1 67 1 0
#> 140 12.68 1 59 1 0
#> 32.1 20.90 1 37 1 0
#> 92.1 22.92 1 47 0 1
#> 99.1 21.19 1 38 0 1
#> 81 14.06 1 34 0 0
#> 90.2 20.94 1 50 0 1
#> 164.1 23.60 1 76 0 1
#> 123 13.00 1 44 1 0
#> 169 22.41 1 46 0 0
#> 168 23.72 1 70 0 0
#> 85.1 16.44 1 36 0 0
#> 76 19.22 1 54 0 1
#> 197.1 21.60 1 69 1 0
#> 180 14.82 1 37 0 0
#> 111.2 17.45 1 47 0 1
#> 61 10.12 1 36 0 1
#> 108 18.29 1 39 0 1
#> 76.1 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 125.2 15.65 1 67 1 0
#> 113.1 22.86 1 34 0 0
#> 24 23.89 1 38 0 0
#> 68.1 20.62 1 44 0 0
#> 15.1 22.68 1 48 0 0
#> 97 19.14 1 65 0 1
#> 69 23.23 1 25 0 1
#> 90.3 20.94 1 50 0 1
#> 105 19.75 1 60 0 0
#> 63 22.77 1 31 1 0
#> 158 20.14 1 74 1 0
#> 56 12.21 1 60 0 0
#> 134 17.81 1 47 1 0
#> 14 12.89 1 21 0 0
#> 149 8.37 1 33 1 0
#> 111.3 17.45 1 47 0 1
#> 150 20.33 1 48 0 0
#> 105.1 19.75 1 60 0 0
#> 101 9.97 1 10 0 1
#> 188.1 16.16 1 46 0 1
#> 39 15.59 1 37 0 1
#> 194 22.40 1 38 0 1
#> 92.2 22.92 1 47 0 1
#> 36.1 21.19 1 48 0 1
#> 198 24.00 0 66 0 1
#> 156 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 174 24.00 0 49 1 0
#> 119 24.00 0 17 0 0
#> 54 24.00 0 53 1 0
#> 65 24.00 0 57 1 0
#> 137 24.00 0 45 1 0
#> 75 24.00 0 21 1 0
#> 34 24.00 0 36 0 0
#> 67 24.00 0 25 0 0
#> 28 24.00 0 67 1 0
#> 17 24.00 0 38 0 1
#> 28.1 24.00 0 67 1 0
#> 147 24.00 0 76 1 0
#> 12 24.00 0 63 0 0
#> 112 24.00 0 61 0 0
#> 7 24.00 0 37 1 0
#> 102 24.00 0 49 0 0
#> 198.1 24.00 0 66 0 1
#> 165 24.00 0 47 0 0
#> 144 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 152 24.00 0 36 0 1
#> 64 24.00 0 43 0 0
#> 17.1 24.00 0 38 0 1
#> 7.1 24.00 0 37 1 0
#> 73 24.00 0 NA 0 1
#> 72 24.00 0 40 0 1
#> 161 24.00 0 45 0 0
#> 135 24.00 0 58 1 0
#> 196 24.00 0 19 0 0
#> 73.1 24.00 0 NA 0 1
#> 65.1 24.00 0 57 1 0
#> 83 24.00 0 6 0 0
#> 34.1 24.00 0 36 0 0
#> 148 24.00 0 61 1 0
#> 121 24.00 0 57 1 0
#> 62 24.00 0 71 0 0
#> 122 24.00 0 66 0 0
#> 172 24.00 0 41 0 0
#> 112.1 24.00 0 61 0 0
#> 71 24.00 0 51 0 0
#> 122.1 24.00 0 66 0 0
#> 119.1 24.00 0 17 0 0
#> 11 24.00 0 42 0 1
#> 98 24.00 0 34 1 0
#> 67.1 24.00 0 25 0 0
#> 11.1 24.00 0 42 0 1
#> 98.1 24.00 0 34 1 0
#> 104 24.00 0 50 1 0
#> 172.1 24.00 0 41 0 0
#> 146 24.00 0 63 1 0
#> 48 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 103 24.00 0 56 1 0
#> 103.1 24.00 0 56 1 0
#> 193 24.00 0 45 0 1
#> 11.2 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 38 24.00 0 31 1 0
#> 142 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 131 24.00 0 66 0 0
#> 112.2 24.00 0 61 0 0
#> 151 24.00 0 42 0 0
#> 121.1 24.00 0 57 1 0
#> 11.3 24.00 0 42 0 1
#> 9 24.00 0 31 1 0
#> 83.1 24.00 0 6 0 0
#> 71.1 24.00 0 51 0 0
#> 65.2 24.00 0 57 1 0
#> 146.1 24.00 0 63 1 0
#> 71.2 24.00 0 51 0 0
#> 3.1 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 163 24.00 0 66 0 0
#> 73.2 24.00 0 NA 0 1
#> 3.2 24.00 0 31 1 0
#> 21 24.00 0 47 0 0
#> 146.2 24.00 0 63 1 0
#> 34.2 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 54.1 24.00 0 53 1 0
#> 119.2 24.00 0 17 0 0
#> 102.1 24.00 0 49 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.978 NA NA NA
#> 2 age, Cure model 0.0145 NA NA NA
#> 3 grade_ii, Cure model 0.309 NA NA NA
#> 4 grade_iii, Cure model 1.42 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00385 NA NA NA
#> 2 grade_ii, Survival model 0.884 NA NA NA
#> 3 grade_iii, Survival model 0.277 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97822 0.01452 0.30921 1.42337
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.5
#> Residual Deviance: 244.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.97821651 0.01451977 0.30921445 1.42337200
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003850403 0.884318249 0.277342271
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.788332047 0.032887712 0.673483668 0.372993941 0.905617232 0.587462116
#> [7] 0.890332322 0.690403596 0.690403596 0.631197095 0.503904662 0.353941310
#> [13] 0.985786404 0.796317338 0.503904662 0.992894305 0.314598046 0.851842147
#> [19] 0.274821612 0.062662909 0.401085585 0.264095203 0.942812373 0.928113410
#> [25] 0.639981340 0.522600330 0.723679755 0.522600330 0.723679755 0.971506519
#> [31] 0.772404072 0.639981340 0.622399424 0.274821612 0.104655648 0.252934091
#> [37] 0.639981340 0.812286146 0.928113410 0.756246608 0.230223326 0.971506519
#> [43] 0.859637267 0.466456940 0.690403596 0.429266655 0.560342529 0.867429323
#> [49] 0.429266655 0.690403596 0.764362206 0.382387556 0.018333818 0.314598046
#> [55] 0.905617232 0.141260934 0.942812373 0.550871615 0.587462116 0.867429323
#> [61] 0.560342529 0.179942235 0.942812373 0.836121176 0.353941310 0.104655648
#> [67] 0.274821612 0.804296879 0.314598046 0.062662909 0.820282906 0.204609389
#> [73] 0.047206288 0.639981340 0.475887500 0.230223326 0.780362663 0.587462116
#> [79] 0.897979616 0.541407434 0.475887500 0.882679758 0.723679755 0.141260934
#> [85] 0.005761433 0.382387556 0.179942235 0.494509308 0.090142611 0.314598046
#> [91] 0.447782110 0.167456391 0.419975319 0.843974110 0.578470765 0.828199100
#> [97] 0.964338078 0.587462116 0.410512113 0.447782110 0.920605219 0.673483668
#> [103] 0.748047271 0.217469027 0.104655648 0.274821612 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 133 86 188 190 145 111 52 26 26.1 181 8 32 25
#> 14.65 23.81 16.16 20.81 10.07 17.45 10.42 15.77 15.77 16.46 18.43 20.90 6.32
#> 13 8.1 91 90 49 36 164 128 153 183 187 192 88
#> 14.34 18.43 5.33 20.94 12.19 21.19 23.60 20.35 21.33 9.24 9.92 16.44 18.37
#> 125 88.1 125.1 77 18 85 106 99 92 139 192.1 155 187.1
#> 15.65 18.37 15.65 7.27 15.21 16.44 16.67 21.19 22.92 21.49 16.44 13.08 9.92
#> 167 197 77.1 43 55 26.2 166 41 107 166.1 26.3 29 68
#> 15.55 21.60 7.27 12.10 19.34 15.77 19.98 18.02 11.18 19.98 15.77 15.45 20.62
#> 78 90.1 145.1 113 183.1 51 111.1 107.1 41.1 15 183.2 140 32.1
#> 23.88 20.94 10.07 22.86 9.24 18.23 17.45 11.18 18.02 22.68 9.24 12.68 20.90
#> 92.1 99.1 81 90.2 164.1 123 169 168 85.1 76 197.1 180 111.2
#> 22.92 21.19 14.06 20.94 23.60 13.00 22.41 23.72 16.44 19.22 21.60 14.82 17.45
#> 61 108 76.1 159 125.2 113.1 24 68.1 15.1 97 69 90.3 105
#> 10.12 18.29 19.22 10.55 15.65 22.86 23.89 20.62 22.68 19.14 23.23 20.94 19.75
#> 63 158 56 134 14 149 111.3 150 105.1 101 188.1 39 194
#> 22.77 20.14 12.21 17.81 12.89 8.37 17.45 20.33 19.75 9.97 16.16 15.59 22.40
#> 92.2 36.1 198 156 33 174 119 54 65 137 75 34 67
#> 22.92 21.19 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 17 28.1 147 12 112 7 102 198.1 165 144 80 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64 17.1 7.1 72 161 135 196 65.1 83 34.1 148 121 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 122 172 112.1 71 122.1 119.1 11 98 67.1 11.1 98.1 104 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 146 48 165.1 103 103.1 193 11.2 87 38 142 33.1 3 191
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 131 112.2 151 121.1 11.3 9 83.1 71.1 65.2 146.1 71.2 3.1 193.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163 3.2 21 146.2 34.2 1 54.1 119.2 102.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[90]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.003705079 0.494852878 0.221731398
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.253298261 -0.003285363 0.403862002
#> grade_iii, Cure model
#> 1.677948635
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 37 12.52 1 57 1 0
#> 88 18.37 1 47 0 0
#> 97 19.14 1 65 0 1
#> 97.1 19.14 1 65 0 1
#> 128 20.35 1 35 0 1
#> 155 13.08 1 26 0 0
#> 61 10.12 1 36 0 1
#> 139 21.49 1 63 1 0
#> 187 9.92 1 39 1 0
#> 159 10.55 1 50 0 1
#> 181 16.46 1 45 0 1
#> 69 23.23 1 25 0 1
#> 39 15.59 1 37 0 1
#> 23 16.92 1 61 0 0
#> 40 18.00 1 28 1 0
#> 113 22.86 1 34 0 0
#> 45 17.42 1 54 0 1
#> 24 23.89 1 38 0 0
#> 125 15.65 1 67 1 0
#> 150 20.33 1 48 0 0
#> 167 15.55 1 56 1 0
#> 195 11.76 1 NA 1 0
#> 106 16.67 1 49 1 0
#> 127 3.53 1 62 0 1
#> 179 18.63 1 42 0 0
#> 154 12.63 1 20 1 0
#> 92 22.92 1 47 0 1
#> 85 16.44 1 36 0 0
#> 60 13.15 1 38 1 0
#> 14 12.89 1 21 0 0
#> 123 13.00 1 44 1 0
#> 86 23.81 1 58 0 1
#> 123.1 13.00 1 44 1 0
#> 197 21.60 1 69 1 0
#> 41 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 40.1 18.00 1 28 1 0
#> 96 14.54 1 33 0 1
#> 93 10.33 1 52 0 1
#> 30 17.43 1 78 0 0
#> 154.1 12.63 1 20 1 0
#> 134 17.81 1 47 1 0
#> 4 17.64 1 NA 0 1
#> 81 14.06 1 34 0 0
#> 106.1 16.67 1 49 1 0
#> 108 18.29 1 39 0 1
#> 77 7.27 1 67 0 1
#> 63 22.77 1 31 1 0
#> 51 18.23 1 83 0 1
#> 15 22.68 1 48 0 0
#> 89 11.44 1 NA 0 0
#> 93.1 10.33 1 52 0 1
#> 199 19.81 1 NA 0 1
#> 108.1 18.29 1 39 0 1
#> 159.1 10.55 1 50 0 1
#> 150.1 20.33 1 48 0 0
#> 157 15.10 1 47 0 0
#> 133 14.65 1 57 0 0
#> 187.1 9.92 1 39 1 0
#> 50 10.02 1 NA 1 0
#> 30.1 17.43 1 78 0 0
#> 8 18.43 1 32 0 0
#> 6 15.64 1 39 0 0
#> 51.1 18.23 1 83 0 1
#> 123.2 13.00 1 44 1 0
#> 170 19.54 1 43 0 1
#> 117 17.46 1 26 0 1
#> 45.1 17.42 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 26 15.77 1 49 0 1
#> 81.1 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 106.2 16.67 1 49 1 0
#> 40.2 18.00 1 28 1 0
#> 130 16.47 1 53 0 1
#> 189 10.51 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 68 20.62 1 44 0 0
#> 136 21.83 1 43 0 1
#> 76 19.22 1 54 0 1
#> 58 19.34 1 39 0 0
#> 108.2 18.29 1 39 0 1
#> 153 21.33 1 55 1 0
#> 42 12.43 1 49 0 1
#> 55 19.34 1 69 0 1
#> 113.1 22.86 1 34 0 0
#> 76.1 19.22 1 54 0 1
#> 51.2 18.23 1 83 0 1
#> 134.1 17.81 1 47 1 0
#> 106.3 16.67 1 49 1 0
#> 171 16.57 1 41 0 1
#> 117.1 17.46 1 26 0 1
#> 108.3 18.29 1 39 0 1
#> 181.1 16.46 1 45 0 1
#> 15.1 22.68 1 48 0 0
#> 129 23.41 1 53 1 0
#> 199.1 19.81 1 NA 0 1
#> 79.2 16.23 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 16 8.71 1 71 0 1
#> 43 12.10 1 61 0 1
#> 89.1 11.44 1 NA 0 0
#> 86.1 23.81 1 58 0 1
#> 183 9.24 1 67 1 0
#> 153.1 21.33 1 55 1 0
#> 8.1 18.43 1 32 0 0
#> 157.1 15.10 1 47 0 0
#> 92.1 22.92 1 47 0 1
#> 92.2 22.92 1 47 0 1
#> 183.1 9.24 1 67 1 0
#> 58.1 19.34 1 39 0 0
#> 102 24.00 0 49 0 0
#> 200 24.00 0 64 0 0
#> 94 24.00 0 51 0 1
#> 116 24.00 0 58 0 1
#> 141 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 115 24.00 0 NA 1 0
#> 47 24.00 0 38 0 1
#> 185 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 182 24.00 0 35 0 0
#> 141.1 24.00 0 44 1 0
#> 47.1 24.00 0 38 0 1
#> 67 24.00 0 25 0 0
#> 21 24.00 0 47 0 0
#> 87 24.00 0 27 0 0
#> 161 24.00 0 45 0 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 109 24.00 0 48 0 0
#> 131 24.00 0 66 0 0
#> 74 24.00 0 43 0 1
#> 46 24.00 0 71 0 0
#> 115.1 24.00 0 NA 1 0
#> 151 24.00 0 42 0 0
#> 73 24.00 0 NA 0 1
#> 118 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 178 24.00 0 52 1 0
#> 31 24.00 0 36 0 1
#> 132 24.00 0 55 0 0
#> 20 24.00 0 46 1 0
#> 48 24.00 0 31 1 0
#> 119.1 24.00 0 17 0 0
#> 131.1 24.00 0 66 0 0
#> 122 24.00 0 66 0 0
#> 75.1 24.00 0 21 1 0
#> 1 24.00 0 23 1 0
#> 135 24.00 0 58 1 0
#> 53 24.00 0 32 0 1
#> 132.1 24.00 0 55 0 0
#> 1.1 24.00 0 23 1 0
#> 38 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 138 24.00 0 44 1 0
#> 74.1 24.00 0 43 0 1
#> 135.1 24.00 0 58 1 0
#> 174 24.00 0 49 1 0
#> 142 24.00 0 53 0 0
#> 160 24.00 0 31 1 0
#> 1.2 24.00 0 23 1 0
#> 112 24.00 0 61 0 0
#> 131.2 24.00 0 66 0 0
#> 46.1 24.00 0 71 0 0
#> 148 24.00 0 61 1 0
#> 198 24.00 0 66 0 1
#> 198.1 24.00 0 66 0 1
#> 147 24.00 0 76 1 0
#> 44 24.00 0 56 0 0
#> 83 24.00 0 6 0 0
#> 103 24.00 0 56 1 0
#> 2 24.00 0 9 0 0
#> 161.1 24.00 0 45 0 0
#> 172 24.00 0 41 0 0
#> 174.1 24.00 0 49 1 0
#> 165 24.00 0 47 0 0
#> 22 24.00 0 52 1 0
#> 115.2 24.00 0 NA 1 0
#> 12 24.00 0 63 0 0
#> 176 24.00 0 43 0 1
#> 33 24.00 0 53 0 0
#> 142.1 24.00 0 53 0 0
#> 33.1 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 64 24.00 0 43 0 0
#> 135.2 24.00 0 58 1 0
#> 12.1 24.00 0 63 0 0
#> 80 24.00 0 41 0 0
#> 200.1 24.00 0 64 0 0
#> 27.1 24.00 0 63 1 0
#> 122.2 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 193 24.00 0 45 0 1
#> 38.1 24.00 0 31 1 0
#> 20.1 24.00 0 46 1 0
#> 196 24.00 0 19 0 0
#> 174.2 24.00 0 49 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.253 NA NA NA
#> 2 age, Cure model -0.00329 NA NA NA
#> 3 grade_ii, Cure model 0.404 NA NA NA
#> 4 grade_iii, Cure model 1.68 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00371 NA NA NA
#> 2 grade_ii, Survival model 0.495 NA NA NA
#> 3 grade_iii, Survival model 0.222 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.253298 -0.003285 0.403862 1.677949
#>
#> Degrees of Freedom: 187 Total (i.e. Null); 184 Residual
#> Null Deviance: 258.5
#> Residual Deviance: 238.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.253298261 -0.003285363 0.403862002 1.677948635
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.003705079 0.494852878 0.221731398
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.841888638 0.348041138 0.298115818 0.298115818 0.209640010 0.779268104
#> [7] 0.912699226 0.170156673 0.939113531 0.868531893 0.605471136 0.056635460
#> [13] 0.697190934 0.540759748 0.436715780 0.097054704 0.521812158 0.007065226
#> [19] 0.678903100 0.219541329 0.706332428 0.550352320 0.991288544 0.317909797
#> [25] 0.824154351 0.068232704 0.623942125 0.770141273 0.815136941 0.788404763
#> [31] 0.022339832 0.788404763 0.159687988 0.426693481 0.921555064 0.642582036
#> [37] 0.436715780 0.742756585 0.895057744 0.502849571 0.824154351 0.465182313
#> [43] 0.751904506 0.550352320 0.358251806 0.982577697 0.117904415 0.397045626
#> [49] 0.128387701 0.895057744 0.358251806 0.868531893 0.219541329 0.715434707
#> [55] 0.733596868 0.939113531 0.502849571 0.328011904 0.688038841 0.397045626
#> [61] 0.788404763 0.239180480 0.484064839 0.521812158 0.642582036 0.669732849
#> [67] 0.751904506 0.633264364 0.550352320 0.436715780 0.596147925 0.886187929
#> [73] 0.199693490 0.149030827 0.278347142 0.249183405 0.358251806 0.180436640
#> [79] 0.850772126 0.249183405 0.097054704 0.278347142 0.397045626 0.465182313
#> [85] 0.550352320 0.586820971 0.484064839 0.358251806 0.605471136 0.128387701
#> [91] 0.044711915 0.642582036 0.921555064 0.973868870 0.859651814 0.022339832
#> [97] 0.956535343 0.180436640 0.328011904 0.715434707 0.068232704 0.068232704
#> [103] 0.956535343 0.249183405 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000
#>
#> $Time
#> 37 88 97 97.1 128 155 61 139 187 159 181 69 39
#> 12.52 18.37 19.14 19.14 20.35 13.08 10.12 21.49 9.92 10.55 16.46 23.23 15.59
#> 23 40 113 45 24 125 150 167 106 127 179 154 92
#> 16.92 18.00 22.86 17.42 23.89 15.65 20.33 15.55 16.67 3.53 18.63 12.63 22.92
#> 85 60 14 123 86 123.1 197 41 101 79 40.1 96 93
#> 16.44 13.15 12.89 13.00 23.81 13.00 21.60 18.02 9.97 16.23 18.00 14.54 10.33
#> 30 154.1 134 81 106.1 108 77 63 51 15 93.1 108.1 159.1
#> 17.43 12.63 17.81 14.06 16.67 18.29 7.27 22.77 18.23 22.68 10.33 18.29 10.55
#> 150.1 157 133 187.1 30.1 8 6 51.1 123.2 170 117 45.1 79.1
#> 20.33 15.10 14.65 9.92 17.43 18.43 15.64 18.23 13.00 19.54 17.46 17.42 16.23
#> 26 81.1 5 106.2 40.2 130 52 68 136 76 58 108.2 153
#> 15.77 14.06 16.43 16.67 18.00 16.47 10.42 20.62 21.83 19.22 19.34 18.29 21.33
#> 42 55 113.1 76.1 51.2 134.1 106.3 171 117.1 108.3 181.1 15.1 129
#> 12.43 19.34 22.86 19.22 18.23 17.81 16.67 16.57 17.46 18.29 16.46 22.68 23.41
#> 79.2 101.1 16 43 86.1 183 153.1 8.1 157.1 92.1 92.2 183.1 58.1
#> 16.23 9.97 8.71 12.10 23.81 9.24 21.33 18.43 15.10 22.92 22.92 9.24 19.34
#> 102 200 94 116 141 75 47 185 35 182 141.1 47.1 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 21 87 161 27 119 109 131 74 46 151 118 156 178
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 31 132 20 48 119.1 131.1 122 75.1 1 135 53 132.1 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 95 138 74.1 135.1 174 142 160 1.2 112 131.2 46.1 148
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 198.1 147 44 83 103 2 161.1 172 174.1 165 22 12
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 176 33 142.1 33.1 65 122.1 64 135.2 12.1 80 200.1 27.1 122.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 193 38.1 20.1 196 174.2
#> 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[91]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.01189639 0.75851954 0.71488521
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.371984354 0.002112717 0.342603533
#> grade_iii, Cure model
#> 0.983823925
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 4 17.64 1 NA 0 1
#> 106 16.67 1 49 1 0
#> 159 10.55 1 50 0 1
#> 155 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 149 8.37 1 33 1 0
#> 108 18.29 1 39 0 1
#> 166 19.98 1 48 0 0
#> 199 19.81 1 NA 0 1
#> 180 14.82 1 37 0 0
#> 89 11.44 1 NA 0 0
#> 57 14.46 1 45 0 1
#> 13 14.34 1 54 0 1
#> 123 13.00 1 44 1 0
#> 113 22.86 1 34 0 0
#> 150 20.33 1 48 0 0
#> 61 10.12 1 36 0 1
#> 188 16.16 1 46 0 1
#> 89.1 11.44 1 NA 0 0
#> 169 22.41 1 46 0 0
#> 78 23.88 1 43 0 0
#> 15 22.68 1 48 0 0
#> 181 16.46 1 45 0 1
#> 42 12.43 1 49 0 1
#> 157 15.10 1 47 0 0
#> 42.1 12.43 1 49 0 1
#> 97 19.14 1 65 0 1
#> 50 10.02 1 NA 1 0
#> 90 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 113.1 22.86 1 34 0 0
#> 99 21.19 1 38 0 1
#> 13.1 14.34 1 54 0 1
#> 189 10.51 1 NA 1 0
#> 60 13.15 1 38 1 0
#> 55 19.34 1 69 0 1
#> 192 16.44 1 31 1 0
#> 175 21.91 1 43 0 0
#> 63 22.77 1 31 1 0
#> 125 15.65 1 67 1 0
#> 127 3.53 1 62 0 1
#> 110 17.56 1 65 0 1
#> 179 18.63 1 42 0 0
#> 58 19.34 1 39 0 0
#> 124 9.73 1 NA 1 0
#> 113.2 22.86 1 34 0 0
#> 37 12.52 1 57 1 0
#> 194 22.40 1 38 0 1
#> 30 17.43 1 78 0 0
#> 158 20.14 1 74 1 0
#> 85 16.44 1 36 0 0
#> 66 22.13 1 53 0 0
#> 14 12.89 1 21 0 0
#> 49 12.19 1 48 1 0
#> 18 15.21 1 49 1 0
#> 81 14.06 1 34 0 0
#> 5 16.43 1 51 0 1
#> 150.1 20.33 1 48 0 0
#> 140 12.68 1 59 1 0
#> 36 21.19 1 48 0 1
#> 30.1 17.43 1 78 0 0
#> 158.1 20.14 1 74 1 0
#> 129 23.41 1 53 1 0
#> 153 21.33 1 55 1 0
#> 127.1 3.53 1 62 0 1
#> 6 15.64 1 39 0 0
#> 110.1 17.56 1 65 0 1
#> 10 10.53 1 34 0 0
#> 59 10.16 1 NA 1 0
#> 113.3 22.86 1 34 0 0
#> 108.1 18.29 1 39 0 1
#> 79 16.23 1 54 1 0
#> 130 16.47 1 53 0 1
#> 123.1 13.00 1 44 1 0
#> 24 23.89 1 38 0 0
#> 39 15.59 1 37 0 1
#> 158.2 20.14 1 74 1 0
#> 51 18.23 1 83 0 1
#> 113.4 22.86 1 34 0 0
#> 190 20.81 1 42 1 0
#> 125.1 15.65 1 67 1 0
#> 97.1 19.14 1 65 0 1
#> 170 19.54 1 43 0 1
#> 110.2 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 78.1 23.88 1 43 0 0
#> 107 11.18 1 54 1 0
#> 170.1 19.54 1 43 0 1
#> 107.1 11.18 1 54 1 0
#> 50.1 10.02 1 NA 1 0
#> 107.2 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 136 21.83 1 43 0 1
#> 16 8.71 1 71 0 1
#> 58.1 19.34 1 39 0 0
#> 108.2 18.29 1 39 0 1
#> 93 10.33 1 52 0 1
#> 4.1 17.64 1 NA 0 1
#> 43 12.10 1 61 0 1
#> 45 17.42 1 54 0 1
#> 170.2 19.54 1 43 0 1
#> 5.1 16.43 1 51 0 1
#> 58.2 19.34 1 39 0 0
#> 179.1 18.63 1 42 0 0
#> 70 7.38 1 30 1 0
#> 111.1 17.45 1 47 0 1
#> 76 19.22 1 54 0 1
#> 90.1 20.94 1 50 0 1
#> 133 14.65 1 57 0 0
#> 42.2 12.43 1 49 0 1
#> 69 23.23 1 25 0 1
#> 194.1 22.40 1 38 0 1
#> 80 24.00 0 41 0 0
#> 28 24.00 0 67 1 0
#> 132 24.00 0 55 0 0
#> 98 24.00 0 34 1 0
#> 160 24.00 0 31 1 0
#> 112 24.00 0 61 0 0
#> 148 24.00 0 61 1 0
#> 112.1 24.00 0 61 0 0
#> 182 24.00 0 35 0 0
#> 126 24.00 0 48 0 0
#> 34 24.00 0 36 0 0
#> 156 24.00 0 50 1 0
#> 173 24.00 0 19 0 1
#> 147 24.00 0 76 1 0
#> 62 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 95 24.00 0 68 0 1
#> 104 24.00 0 50 1 0
#> 132.1 24.00 0 55 0 0
#> 151 24.00 0 42 0 0
#> 102 24.00 0 49 0 0
#> 120 24.00 0 68 0 1
#> 146 24.00 0 63 1 0
#> 31 24.00 0 36 0 1
#> 2 24.00 0 9 0 0
#> 82 24.00 0 34 0 0
#> 53 24.00 0 32 0 1
#> 119 24.00 0 17 0 0
#> 142 24.00 0 53 0 0
#> 109 24.00 0 48 0 0
#> 82.1 24.00 0 34 0 0
#> 104.1 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 19 24.00 0 57 0 1
#> 21 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 9 24.00 0 31 1 0
#> 161 24.00 0 45 0 0
#> 116 24.00 0 58 0 1
#> 31.1 24.00 0 36 0 1
#> 172 24.00 0 41 0 0
#> 74 24.00 0 43 0 1
#> 191 24.00 0 60 0 1
#> 104.2 24.00 0 50 1 0
#> 80.1 24.00 0 41 0 0
#> 47 24.00 0 38 0 1
#> 135 24.00 0 58 1 0
#> 176 24.00 0 43 0 1
#> 185 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 178 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 146.1 24.00 0 63 1 0
#> 119.1 24.00 0 17 0 0
#> 178.1 24.00 0 52 1 0
#> 67 24.00 0 25 0 0
#> 200.1 24.00 0 64 0 0
#> 120.1 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 72 24.00 0 40 0 1
#> 95.1 24.00 0 68 0 1
#> 80.2 24.00 0 41 0 0
#> 138 24.00 0 44 1 0
#> 80.3 24.00 0 41 0 0
#> 71 24.00 0 51 0 0
#> 172.1 24.00 0 41 0 0
#> 116.1 24.00 0 58 0 1
#> 44.1 24.00 0 56 0 0
#> 165 24.00 0 47 0 0
#> 182.1 24.00 0 35 0 0
#> 115 24.00 0 NA 1 0
#> 9.1 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 21.1 24.00 0 47 0 0
#> 28.1 24.00 0 67 1 0
#> 143 24.00 0 51 0 0
#> 17 24.00 0 38 0 1
#> 84 24.00 0 39 0 1
#> 20.1 24.00 0 46 1 0
#> 74.1 24.00 0 43 0 1
#> 104.3 24.00 0 50 1 0
#> 103 24.00 0 56 1 0
#> 72.1 24.00 0 40 0 1
#> 147.1 24.00 0 76 1 0
#> 119.2 24.00 0 17 0 0
#> 126.1 24.00 0 48 0 0
#> 46 24.00 0 71 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.372 NA NA NA
#> 2 age, Cure model 0.00211 NA NA NA
#> 3 grade_ii, Cure model 0.343 NA NA NA
#> 4 grade_iii, Cure model 0.984 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.0119 NA NA NA
#> 2 grade_ii, Survival model 0.759 NA NA NA
#> 3 grade_iii, Survival model 0.715 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.371984 0.002113 0.342604 0.983824
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.8
#> Residual Deviance: 252.4 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.371984354 0.002112717 0.342603533 0.983823925
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.01189639 0.75851954 0.71488521
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.81574985 0.96807863 0.91841583 0.79015567 0.98757618 0.75035925
#> [7] 0.65997635 0.89109137 0.89910493 0.90305921 0.92222095 0.32311811
#> [13] 0.61628243 0.97794069 0.85775547 0.45738085 0.17638016 0.43873022
#> [19] 0.83033131 0.94067604 0.88706586 0.94067604 0.72487493 0.58552779
#> [25] 0.87893451 0.32311811 0.56259863 0.90305921 0.91460498 0.69024844
#> [31] 0.83504803 0.52107016 0.41944861 0.86213730 0.99386651 0.77408101
#> [37] 0.73768841 0.69024844 0.32311811 0.93704925 0.47549361 0.80054471
#> [43] 0.63568051 0.83504803 0.50599027 0.92965608 0.95119209 0.88302662
#> [49] 0.91075637 0.84431792 0.61628243 0.93337687 0.56259863 0.80054471
#> [55] 0.63568051 0.26512444 0.54973567 0.99386651 0.87055951 0.77408101
#> [61] 0.97137999 0.32311811 0.75035925 0.85331620 0.82554689 0.92222095
#> [67] 0.09334734 0.87476880 0.63568051 0.76826849 0.32311811 0.60626102
#> [73] 0.86213730 0.72487493 0.66809871 0.77408101 0.82068241 0.17638016
#> [79] 0.95811670 0.66809871 0.95811670 0.95811670 0.98118249 0.53586416
#> [85] 0.98439884 0.69024844 0.75035925 0.97467576 0.95467463 0.81073158
#> [91] 0.66809871 0.84431792 0.69024844 0.73768841 0.99073158 0.79015567
#> [97] 0.71802243 0.58552779 0.89510685 0.94067604 0.29658361 0.47549361
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 106 159 155 111 149 108 166 180 57 13 123 113 150
#> 16.67 10.55 13.08 17.45 8.37 18.29 19.98 14.82 14.46 14.34 13.00 22.86 20.33
#> 61 188 169 78 15 181 42 157 42.1 97 90 29 113.1
#> 10.12 16.16 22.41 23.88 22.68 16.46 12.43 15.10 12.43 19.14 20.94 15.45 22.86
#> 99 13.1 60 55 192 175 63 125 127 110 179 58 113.2
#> 21.19 14.34 13.15 19.34 16.44 21.91 22.77 15.65 3.53 17.56 18.63 19.34 22.86
#> 37 194 30 158 85 66 14 49 18 81 5 150.1 140
#> 12.52 22.40 17.43 20.14 16.44 22.13 12.89 12.19 15.21 14.06 16.43 20.33 12.68
#> 36 30.1 158.1 129 153 127.1 6 110.1 10 113.3 108.1 79 130
#> 21.19 17.43 20.14 23.41 21.33 3.53 15.64 17.56 10.53 22.86 18.29 16.23 16.47
#> 123.1 24 39 158.2 51 113.4 190 125.1 97.1 170 110.2 171 78.1
#> 13.00 23.89 15.59 20.14 18.23 22.86 20.81 15.65 19.14 19.54 17.56 16.57 23.88
#> 107 170.1 107.1 107.2 187 136 16 58.1 108.2 93 43 45 170.2
#> 11.18 19.54 11.18 11.18 9.92 21.83 8.71 19.34 18.29 10.33 12.10 17.42 19.54
#> 5.1 58.2 179.1 70 111.1 76 90.1 133 42.2 69 194.1 80 28
#> 16.43 19.34 18.63 7.38 17.45 19.22 20.94 14.65 12.43 23.23 22.40 24.00 24.00
#> 132 98 160 112 148 112.1 182 126 34 156 173 147 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 44 95 104 132.1 151 102 120 146 31 2 82 53 119
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 109 82.1 104.1 122 19 21 200 9 161 116 31.1 172
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 191 104.2 80.1 47 135 176 185 173.1 20 178 94 146.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 119.1 178.1 67 200.1 120.1 64 72 95.1 80.2 138 80.3 71 172.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 116.1 44.1 165 182.1 9.1 87 21.1 28.1 143 17 84 20.1 74.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 104.3 103 72.1 147.1 119.2 126.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[92]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001570814 1.400902163 0.500382486
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.64123617 -0.01602564 0.01938245
#> grade_iii, Cure model
#> 1.16750045
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 10 10.53 1 34 0 0
#> 16 8.71 1 71 0 1
#> 93 10.33 1 52 0 1
#> 150 20.33 1 48 0 0
#> 171 16.57 1 41 0 1
#> 150.1 20.33 1 48 0 0
#> 4 17.64 1 NA 0 1
#> 179 18.63 1 42 0 0
#> 41 18.02 1 40 1 0
#> 43 12.10 1 61 0 1
#> 69 23.23 1 25 0 1
#> 69.1 23.23 1 25 0 1
#> 187 9.92 1 39 1 0
#> 5 16.43 1 51 0 1
#> 23 16.92 1 61 0 0
#> 101 9.97 1 10 0 1
#> 79 16.23 1 54 1 0
#> 78 23.88 1 43 0 0
#> 157 15.10 1 47 0 0
#> 30 17.43 1 78 0 0
#> 106 16.67 1 49 1 0
#> 66 22.13 1 53 0 0
#> 18 15.21 1 49 1 0
#> 159 10.55 1 50 0 1
#> 99 21.19 1 38 0 1
#> 55 19.34 1 69 0 1
#> 108 18.29 1 39 0 1
#> 6 15.64 1 39 0 0
#> 123 13.00 1 44 1 0
#> 155 13.08 1 26 0 0
#> 111 17.45 1 47 0 1
#> 56 12.21 1 60 0 0
#> 130 16.47 1 53 0 1
#> 166 19.98 1 48 0 0
#> 125 15.65 1 67 1 0
#> 15 22.68 1 48 0 0
#> 13 14.34 1 54 0 1
#> 76 19.22 1 54 0 1
#> 164 23.60 1 76 0 1
#> 101.1 9.97 1 10 0 1
#> 89 11.44 1 NA 0 0
#> 194 22.40 1 38 0 1
#> 90 20.94 1 50 0 1
#> 29 15.45 1 68 1 0
#> 70 7.38 1 30 1 0
#> 57 14.46 1 45 0 1
#> 25 6.32 1 34 1 0
#> 40 18.00 1 28 1 0
#> 149 8.37 1 33 1 0
#> 61 10.12 1 36 0 1
#> 189 10.51 1 NA 1 0
#> 76.1 19.22 1 54 0 1
#> 76.2 19.22 1 54 0 1
#> 68 20.62 1 44 0 0
#> 96 14.54 1 33 0 1
#> 24 23.89 1 38 0 0
#> 179.1 18.63 1 42 0 0
#> 183 9.24 1 67 1 0
#> 189.1 10.51 1 NA 1 0
#> 56.1 12.21 1 60 0 0
#> 85 16.44 1 36 0 0
#> 60 13.15 1 38 1 0
#> 192 16.44 1 31 1 0
#> 13.1 14.34 1 54 0 1
#> 41.1 18.02 1 40 1 0
#> 68.1 20.62 1 44 0 0
#> 169 22.41 1 46 0 0
#> 170 19.54 1 43 0 1
#> 23.1 16.92 1 61 0 0
#> 179.2 18.63 1 42 0 0
#> 13.2 14.34 1 54 0 1
#> 68.2 20.62 1 44 0 0
#> 123.1 13.00 1 44 1 0
#> 50 10.02 1 NA 1 0
#> 113 22.86 1 34 0 0
#> 88 18.37 1 47 0 0
#> 133 14.65 1 57 0 0
#> 181 16.46 1 45 0 1
#> 175 21.91 1 43 0 0
#> 68.3 20.62 1 44 0 0
#> 139 21.49 1 63 1 0
#> 55.1 19.34 1 69 0 1
#> 107 11.18 1 54 1 0
#> 199 19.81 1 NA 0 1
#> 56.2 12.21 1 60 0 0
#> 16.1 8.71 1 71 0 1
#> 25.1 6.32 1 34 1 0
#> 93.1 10.33 1 52 0 1
#> 180 14.82 1 37 0 0
#> 170.1 19.54 1 43 0 1
#> 70.1 7.38 1 30 1 0
#> 128 20.35 1 35 0 1
#> 61.1 10.12 1 36 0 1
#> 125.1 15.65 1 67 1 0
#> 49 12.19 1 48 1 0
#> 58 19.34 1 39 0 0
#> 166.1 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 96.1 14.54 1 33 0 1
#> 106.1 16.67 1 49 1 0
#> 136 21.83 1 43 0 1
#> 78.1 23.88 1 43 0 0
#> 59 10.16 1 NA 1 0
#> 60.1 13.15 1 38 1 0
#> 150.2 20.33 1 48 0 0
#> 187.1 9.92 1 39 1 0
#> 78.2 23.88 1 43 0 0
#> 37 12.52 1 57 1 0
#> 188 16.16 1 46 0 1
#> 88.1 18.37 1 47 0 0
#> 55.2 19.34 1 69 0 1
#> 6.1 15.64 1 39 0 0
#> 126 24.00 0 48 0 0
#> 1 24.00 0 23 1 0
#> 193 24.00 0 45 0 1
#> 198 24.00 0 66 0 1
#> 121 24.00 0 57 1 0
#> 94 24.00 0 51 0 1
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 3 24.00 0 31 1 0
#> 65 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 121.1 24.00 0 57 1 0
#> 135 24.00 0 58 1 0
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 34 24.00 0 36 0 0
#> 178 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 9 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 196 24.00 0 19 0 0
#> 27 24.00 0 63 1 0
#> 119 24.00 0 17 0 0
#> 151 24.00 0 42 0 0
#> 62 24.00 0 71 0 0
#> 151.1 24.00 0 42 0 0
#> 156 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 165 24.00 0 47 0 0
#> 116 24.00 0 58 0 1
#> 156.1 24.00 0 50 1 0
#> 22 24.00 0 52 1 0
#> 186 24.00 0 45 1 0
#> 137 24.00 0 45 1 0
#> 21.1 24.00 0 47 0 0
#> 122.1 24.00 0 66 0 0
#> 161 24.00 0 45 0 0
#> 200 24.00 0 64 0 0
#> 185.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 122.2 24.00 0 66 0 0
#> 109 24.00 0 48 0 0
#> 95 24.00 0 68 0 1
#> 131 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 95.1 24.00 0 68 0 1
#> 34.1 24.00 0 36 0 0
#> 138 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 62.1 24.00 0 71 0 0
#> 22.1 24.00 0 52 1 0
#> 33 24.00 0 53 0 0
#> 156.2 24.00 0 50 1 0
#> 122.3 24.00 0 66 0 0
#> 146 24.00 0 63 1 0
#> 162.1 24.00 0 51 0 0
#> 161.1 24.00 0 45 0 0
#> 20 24.00 0 46 1 0
#> 200.1 24.00 0 64 0 0
#> 151.2 24.00 0 42 0 0
#> 47 24.00 0 38 0 1
#> 182 24.00 0 35 0 0
#> 64 24.00 0 43 0 0
#> 162.2 24.00 0 51 0 0
#> 62.2 24.00 0 71 0 0
#> 62.3 24.00 0 71 0 0
#> 121.2 24.00 0 57 1 0
#> 151.3 24.00 0 42 0 0
#> 3.1 24.00 0 31 1 0
#> 160.1 24.00 0 31 1 0
#> 82 24.00 0 34 0 0
#> 19 24.00 0 57 0 1
#> 120 24.00 0 68 0 1
#> 17 24.00 0 38 0 1
#> 135.1 24.00 0 58 1 0
#> 165.1 24.00 0 47 0 0
#> 122.4 24.00 0 66 0 0
#> 31 24.00 0 36 0 1
#> 33.1 24.00 0 53 0 0
#> 67 24.00 0 25 0 0
#> 9.1 24.00 0 31 1 0
#> 146.1 24.00 0 63 1 0
#> 12 24.00 0 63 0 0
#> 200.2 24.00 0 64 0 0
#> 119.1 24.00 0 17 0 0
#> 104 24.00 0 50 1 0
#> 11 24.00 0 42 0 1
#> 1.1 24.00 0 23 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.641 NA NA NA
#> 2 age, Cure model -0.0160 NA NA NA
#> 3 grade_ii, Cure model 0.0194 NA NA NA
#> 4 grade_iii, Cure model 1.17 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00157 NA NA NA
#> 2 grade_ii, Survival model 1.40 NA NA NA
#> 3 grade_iii, Survival model 0.500 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.64124 -0.01603 0.01938 1.16750
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.5
#> Residual Deviance: 251.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.64123617 -0.01602564 0.01938245 1.16750045
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001570814 1.400902163 0.500382486
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.90797518 0.96398359 0.91373561 0.34635647 0.65173417 0.34635647
#> [7] 0.50437128 0.56895786 0.89055742 0.11060296 0.11060296 0.94772456
#> [13] 0.69334634 0.61620324 0.93647752 0.70143267 0.04098364 0.76059844
#> [19] 0.60693361 0.63465344 0.20379680 0.75359475 0.90221664 0.26276881
#> [25] 0.42879281 0.55813121 0.73172770 0.84217576 0.83565779 0.59768027
#> [31] 0.86674415 0.66026970 0.38158787 0.71706607 0.15629624 0.80238148
#> [37] 0.47241458 0.09128652 0.93647752 0.18841302 0.27535864 0.74640681
#> [43] 0.97991397 0.79546769 0.99010200 0.58835010 0.97464902 0.92514560
#> [49] 0.47241458 0.47241458 0.28765362 0.78163595 0.01417762 0.50437128
#> [55] 0.95860769 0.86674415 0.67717001 0.82267671 0.67717001 0.80238148
#> [61] 0.56895786 0.28765362 0.17230196 0.40556194 0.61620324 0.50437128
#> [67] 0.80238148 0.28765362 0.84217576 0.14040999 0.53645842 0.77461862
#> [73] 0.66874851 0.21927442 0.28765362 0.24983602 0.42879281 0.89643875
#> [79] 0.86674415 0.96398359 0.99010200 0.91373561 0.76760672 0.40556194
#> [85] 0.97991397 0.33428381 0.92514560 0.71706607 0.88465666 0.42879281
#> [91] 0.38158787 0.85462611 0.78163595 0.63465344 0.23482415 0.04098364
#> [97] 0.82267671 0.34635647 0.94772456 0.04098364 0.86074294 0.70927238
#> [103] 0.53645842 0.42879281 0.73172770 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 10 16 93 150 171 150.1 179 41 43 69 69.1 187 5
#> 10.53 8.71 10.33 20.33 16.57 20.33 18.63 18.02 12.10 23.23 23.23 9.92 16.43
#> 23 101 79 78 157 30 106 66 18 159 99 55 108
#> 16.92 9.97 16.23 23.88 15.10 17.43 16.67 22.13 15.21 10.55 21.19 19.34 18.29
#> 6 123 155 111 56 130 166 125 15 13 76 164 101.1
#> 15.64 13.00 13.08 17.45 12.21 16.47 19.98 15.65 22.68 14.34 19.22 23.60 9.97
#> 194 90 29 70 57 25 40 149 61 76.1 76.2 68 96
#> 22.40 20.94 15.45 7.38 14.46 6.32 18.00 8.37 10.12 19.22 19.22 20.62 14.54
#> 24 179.1 183 56.1 85 60 192 13.1 41.1 68.1 169 170 23.1
#> 23.89 18.63 9.24 12.21 16.44 13.15 16.44 14.34 18.02 20.62 22.41 19.54 16.92
#> 179.2 13.2 68.2 123.1 113 88 133 181 175 68.3 139 55.1 107
#> 18.63 14.34 20.62 13.00 22.86 18.37 14.65 16.46 21.91 20.62 21.49 19.34 11.18
#> 56.2 16.1 25.1 93.1 180 170.1 70.1 128 61.1 125.1 49 58 166.1
#> 12.21 8.71 6.32 10.33 14.82 19.54 7.38 20.35 10.12 15.65 12.19 19.34 19.98
#> 154 96.1 106.1 136 78.1 60.1 150.2 187.1 78.2 37 188 88.1 55.2
#> 12.63 14.54 16.67 21.83 23.88 13.15 20.33 9.92 23.88 12.52 16.16 18.37 19.34
#> 6.1 126 1 193 198 121 94 2 142 3 65 160 121.1
#> 15.64 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 135 185 21 34 178 122 9 193.1 196 27 119 151 62
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 151.1 156 176 165 116 156.1 22 186 137 21.1 122.1 161 200
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 185.1 71 122.2 109 95 131 162 95.1 34.1 138 62.1 22.1 33
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 156.2 122.3 146 162.1 161.1 20 200.1 151.2 47 182 64 162.2 62.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 62.3 121.2 151.3 3.1 160.1 82 19 120 17 135.1 165.1 122.4 31
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 33.1 67 9.1 146.1 12 200.2 119.1 104 11 1.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[93]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001536419 0.904944617 0.274741585
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.491203276 0.005982681 -0.134505061
#> grade_iii, Cure model
#> 1.305204407
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 91 5.33 1 61 0 1
#> 4 17.64 1 NA 0 1
#> 133 14.65 1 57 0 0
#> 101 9.97 1 10 0 1
#> 56 12.21 1 60 0 0
#> 169 22.41 1 46 0 0
#> 166 19.98 1 48 0 0
#> 99 21.19 1 38 0 1
#> 114 13.68 1 NA 0 0
#> 113 22.86 1 34 0 0
#> 68 20.62 1 44 0 0
#> 194 22.40 1 38 0 1
#> 18 15.21 1 49 1 0
#> 40 18.00 1 28 1 0
#> 66 22.13 1 53 0 0
#> 79 16.23 1 54 1 0
#> 101.1 9.97 1 10 0 1
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 30 17.43 1 78 0 0
#> 188 16.16 1 46 0 1
#> 5 16.43 1 51 0 1
#> 111 17.45 1 47 0 1
#> 97 19.14 1 65 0 1
#> 127 3.53 1 62 0 1
#> 164 23.60 1 76 0 1
#> 187 9.92 1 39 1 0
#> 56.1 12.21 1 60 0 0
#> 130 16.47 1 53 0 1
#> 4.1 17.64 1 NA 0 1
#> 110 17.56 1 65 0 1
#> 189 10.51 1 NA 1 0
#> 79.1 16.23 1 54 1 0
#> 189.1 10.51 1 NA 1 0
#> 159 10.55 1 50 0 1
#> 140 12.68 1 59 1 0
#> 169.1 22.41 1 46 0 0
#> 169.2 22.41 1 46 0 0
#> 155 13.08 1 26 0 0
#> 105 19.75 1 60 0 0
#> 58 19.34 1 39 0 0
#> 199 19.81 1 NA 0 1
#> 107 11.18 1 54 1 0
#> 145 10.07 1 65 1 0
#> 41 18.02 1 40 1 0
#> 56.2 12.21 1 60 0 0
#> 70 7.38 1 30 1 0
#> 180 14.82 1 37 0 0
#> 127.1 3.53 1 62 0 1
#> 136 21.83 1 43 0 1
#> 49 12.19 1 48 1 0
#> 50 10.02 1 NA 1 0
#> 24 23.89 1 38 0 0
#> 128 20.35 1 35 0 1
#> 66.1 22.13 1 53 0 0
#> 189.2 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 128.1 20.35 1 35 0 1
#> 179 18.63 1 42 0 0
#> 88 18.37 1 47 0 0
#> 133.1 14.65 1 57 0 0
#> 99.1 21.19 1 38 0 1
#> 59 10.16 1 NA 1 0
#> 114.1 13.68 1 NA 0 0
#> 99.2 21.19 1 38 0 1
#> 92 22.92 1 47 0 1
#> 77 7.27 1 67 0 1
#> 18.1 15.21 1 49 1 0
#> 26 15.77 1 49 0 1
#> 175 21.91 1 43 0 0
#> 36 21.19 1 48 0 1
#> 188.1 16.16 1 46 0 1
#> 101.2 9.97 1 10 0 1
#> 88.1 18.37 1 47 0 0
#> 42 12.43 1 49 0 1
#> 15 22.68 1 48 0 0
#> 188.2 16.16 1 46 0 1
#> 90 20.94 1 50 0 1
#> 180.1 14.82 1 37 0 0
#> 36.1 21.19 1 48 0 1
#> 52 10.42 1 52 0 1
#> 49.1 12.19 1 48 1 0
#> 15.1 22.68 1 48 0 0
#> 26.1 15.77 1 49 0 1
#> 105.1 19.75 1 60 0 0
#> 63 22.77 1 31 1 0
#> 45 17.42 1 54 0 1
#> 189.3 10.51 1 NA 1 0
#> 18.2 15.21 1 49 1 0
#> 164.1 23.60 1 76 0 1
#> 13 14.34 1 54 0 1
#> 158 20.14 1 74 1 0
#> 107.1 11.18 1 54 1 0
#> 155.1 13.08 1 26 0 0
#> 199.1 19.81 1 NA 0 1
#> 51 18.23 1 83 0 1
#> 51.1 18.23 1 83 0 1
#> 170 19.54 1 43 0 1
#> 39 15.59 1 37 0 1
#> 154 12.63 1 20 1 0
#> 42.1 12.43 1 49 0 1
#> 192 16.44 1 31 1 0
#> 26.2 15.77 1 49 0 1
#> 45.1 17.42 1 54 0 1
#> 39.1 15.59 1 37 0 1
#> 136.1 21.83 1 43 0 1
#> 99.3 21.19 1 38 0 1
#> 90.1 20.94 1 50 0 1
#> 37 12.52 1 57 1 0
#> 190 20.81 1 42 1 0
#> 6.1 15.64 1 39 0 0
#> 99.4 21.19 1 38 0 1
#> 20 24.00 0 46 1 0
#> 33 24.00 0 53 0 0
#> 84 24.00 0 39 0 1
#> 3 24.00 0 31 1 0
#> 160 24.00 0 31 1 0
#> 48 24.00 0 31 1 0
#> 87 24.00 0 27 0 0
#> 191 24.00 0 60 0 1
#> 94 24.00 0 51 0 1
#> 7 24.00 0 37 1 0
#> 44 24.00 0 56 0 0
#> 12 24.00 0 63 0 0
#> 109 24.00 0 48 0 0
#> 122 24.00 0 66 0 0
#> 104 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 147 24.00 0 76 1 0
#> 138 24.00 0 44 1 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 120 24.00 0 68 0 1
#> 138.1 24.00 0 44 1 0
#> 71 24.00 0 51 0 0
#> 102 24.00 0 49 0 0
#> 178 24.00 0 52 1 0
#> 142 24.00 0 53 0 0
#> 115 24.00 0 NA 1 0
#> 142.1 24.00 0 53 0 0
#> 65 24.00 0 57 1 0
#> 103 24.00 0 56 1 0
#> 144 24.00 0 28 0 1
#> 72 24.00 0 40 0 1
#> 65.1 24.00 0 57 1 0
#> 118 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 148 24.00 0 61 1 0
#> 19.1 24.00 0 57 0 1
#> 185 24.00 0 44 1 0
#> 27 24.00 0 63 1 0
#> 142.2 24.00 0 53 0 0
#> 80 24.00 0 41 0 0
#> 161.1 24.00 0 45 0 0
#> 20.1 24.00 0 46 1 0
#> 112 24.00 0 61 0 0
#> 31 24.00 0 36 0 1
#> 82 24.00 0 34 0 0
#> 196 24.00 0 19 0 0
#> 176 24.00 0 43 0 1
#> 115.1 24.00 0 NA 1 0
#> 20.2 24.00 0 46 1 0
#> 67 24.00 0 25 0 0
#> 27.1 24.00 0 63 1 0
#> 98 24.00 0 34 1 0
#> 64 24.00 0 43 0 0
#> 138.2 24.00 0 44 1 0
#> 17 24.00 0 38 0 1
#> 193 24.00 0 45 0 1
#> 73.1 24.00 0 NA 0 1
#> 172 24.00 0 41 0 0
#> 80.1 24.00 0 41 0 0
#> 54 24.00 0 53 1 0
#> 126 24.00 0 48 0 0
#> 191.1 24.00 0 60 0 1
#> 44.1 24.00 0 56 0 0
#> 80.2 24.00 0 41 0 0
#> 174.1 24.00 0 49 1 0
#> 178.1 24.00 0 52 1 0
#> 165 24.00 0 47 0 0
#> 142.3 24.00 0 53 0 0
#> 131 24.00 0 66 0 0
#> 71.1 24.00 0 51 0 0
#> 65.2 24.00 0 57 1 0
#> 162 24.00 0 51 0 0
#> 11 24.00 0 42 0 1
#> 165.1 24.00 0 47 0 0
#> 185.1 24.00 0 44 1 0
#> 75 24.00 0 21 1 0
#> 46 24.00 0 71 0 0
#> 64.1 24.00 0 43 0 0
#> 131.1 24.00 0 66 0 0
#> 34 24.00 0 36 0 0
#> 109.1 24.00 0 48 0 0
#> 121 24.00 0 57 1 0
#> 82.1 24.00 0 34 0 0
#> 11.1 24.00 0 42 0 1
#> 173 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.491 NA NA NA
#> 2 age, Cure model 0.00598 NA NA NA
#> 3 grade_ii, Cure model -0.135 NA NA NA
#> 4 grade_iii, Cure model 1.31 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00154 NA NA NA
#> 2 grade_ii, Survival model 0.905 NA NA NA
#> 3 grade_iii, Survival model 0.275 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.491203 0.005983 -0.134505 1.305204
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 253.7
#> Residual Deviance: 235.8 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.491203276 0.005982681 -0.134505061 1.305204407
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001536419 0.904944617 0.274741585
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.97823651 0.77548589 0.93404170 0.85695206 0.13702052 0.40007567
#> [7] 0.25174140 0.08163559 0.35760344 0.17429089 0.73436621 0.53352297
#> [13] 0.18747805 0.61997397 0.93404170 0.44152805 0.69056350 0.56272768
#> [19] 0.63789899 0.61059757 0.55302948 0.46200909 0.98552294 0.03558108
#> [25] 0.95624810 0.85695206 0.59157801 0.54329295 0.61997397 0.91133117
#> [31] 0.81684719 0.13702052 0.13702052 0.80032607 0.41048650 0.44152805
#> [37] 0.89615789 0.92652680 0.52350202 0.85695206 0.96363179 0.75897215
#> [43] 0.98552294 0.22653193 0.88064985 0.01232577 0.36850613 0.18747805
#> [49] 0.72569092 0.36850613 0.47232152 0.48264806 0.77548589 0.25174140
#> [55] 0.25174140 0.06540106 0.97093930 0.73436621 0.66434635 0.21320288
#> [61] 0.25174140 0.63789899 0.93404170 0.48264806 0.84111857 0.11142889
#> [67] 0.63789899 0.32439373 0.75897215 0.25174140 0.91893574 0.88064985
#> [73] 0.11142889 0.66434635 0.41048650 0.09804668 0.57244480 0.73436621
#> [79] 0.03558108 0.79202919 0.38968408 0.89615789 0.80032607 0.50314074
#> [85] 0.50314074 0.43113538 0.70818022 0.82504515 0.84111857 0.60118983
#> [91] 0.66434635 0.57244480 0.70818022 0.22653193 0.25174140 0.32439373
#> [97] 0.83313088 0.34672245 0.69056350 0.25174140 0.00000000 0.00000000
#> [103] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 91 133 101 56 169 166 99 113 68 194 18 40 66
#> 5.33 14.65 9.97 12.21 22.41 19.98 21.19 22.86 20.62 22.40 15.21 18.00 22.13
#> 79 101.1 55 6 30 188 5 111 97 127 164 187 56.1
#> 16.23 9.97 19.34 15.64 17.43 16.16 16.43 17.45 19.14 3.53 23.60 9.92 12.21
#> 130 110 79.1 159 140 169.1 169.2 155 105 58 107 145 41
#> 16.47 17.56 16.23 10.55 12.68 22.41 22.41 13.08 19.75 19.34 11.18 10.07 18.02
#> 56.2 70 180 127.1 136 49 24 128 66.1 167 128.1 179 88
#> 12.21 7.38 14.82 3.53 21.83 12.19 23.89 20.35 22.13 15.55 20.35 18.63 18.37
#> 133.1 99.1 99.2 92 77 18.1 26 175 36 188.1 101.2 88.1 42
#> 14.65 21.19 21.19 22.92 7.27 15.21 15.77 21.91 21.19 16.16 9.97 18.37 12.43
#> 15 188.2 90 180.1 36.1 52 49.1 15.1 26.1 105.1 63 45 18.2
#> 22.68 16.16 20.94 14.82 21.19 10.42 12.19 22.68 15.77 19.75 22.77 17.42 15.21
#> 164.1 13 158 107.1 155.1 51 51.1 170 39 154 42.1 192 26.2
#> 23.60 14.34 20.14 11.18 13.08 18.23 18.23 19.54 15.59 12.63 12.43 16.44 15.77
#> 45.1 39.1 136.1 99.3 90.1 37 190 6.1 99.4 20 33 84 3
#> 17.42 15.59 21.83 21.19 20.94 12.52 20.81 15.64 21.19 24.00 24.00 24.00 24.00
#> 160 48 87 191 94 7 44 12 109 122 104 83 147
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138 19 9 174 120 138.1 71 102 178 142 142.1 65 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 144 72 65.1 118 161 148 19.1 185 27 142.2 80 161.1 20.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 112 31 82 196 176 20.2 67 27.1 98 64 138.2 17 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 172 80.1 54 126 191.1 44.1 80.2 174.1 178.1 165 142.3 131 71.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.2 162 11 165.1 185.1 75 46 64.1 131.1 34 109.1 121 82.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 11.1 173
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[94]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.001975163 0.445923569 -0.437121692
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.75163293 0.01240743 0.55758189
#> grade_iii, Cure model
#> 0.59720778
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 58 19.34 1 39 0 0
#> 30 17.43 1 78 0 0
#> 25 6.32 1 34 1 0
#> 18 15.21 1 49 1 0
#> 85 16.44 1 36 0 0
#> 175 21.91 1 43 0 0
#> 91 5.33 1 61 0 1
#> 105 19.75 1 60 0 0
#> 100 16.07 1 60 0 0
#> 183 9.24 1 67 1 0
#> 177 12.53 1 75 0 0
#> 45 17.42 1 54 0 1
#> 89 11.44 1 NA 0 0
#> 153 21.33 1 55 1 0
#> 76 19.22 1 54 0 1
#> 190 20.81 1 42 1 0
#> 199 19.81 1 NA 0 1
#> 105.1 19.75 1 60 0 0
#> 164 23.60 1 76 0 1
#> 153.1 21.33 1 55 1 0
#> 150 20.33 1 48 0 0
#> 97 19.14 1 65 0 1
#> 117 17.46 1 26 0 1
#> 158 20.14 1 74 1 0
#> 184 17.77 1 38 0 0
#> 32 20.90 1 37 1 0
#> 99 21.19 1 38 0 1
#> 90 20.94 1 50 0 1
#> 106 16.67 1 49 1 0
#> 14 12.89 1 21 0 0
#> 89.1 11.44 1 NA 0 0
#> 79 16.23 1 54 1 0
#> 18.1 15.21 1 49 1 0
#> 45.1 17.42 1 54 0 1
#> 8 18.43 1 32 0 0
#> 42 12.43 1 49 0 1
#> 158.1 20.14 1 74 1 0
#> 194 22.40 1 38 0 1
#> 79.1 16.23 1 54 1 0
#> 125 15.65 1 67 1 0
#> 61 10.12 1 36 0 1
#> 179 18.63 1 42 0 0
#> 37 12.52 1 57 1 0
#> 66 22.13 1 53 0 0
#> 88 18.37 1 47 0 0
#> 69 23.23 1 25 0 1
#> 30.1 17.43 1 78 0 0
#> 158.2 20.14 1 74 1 0
#> 170 19.54 1 43 0 1
#> 133 14.65 1 57 0 0
#> 23 16.92 1 61 0 0
#> 49 12.19 1 48 1 0
#> 195 11.76 1 NA 1 0
#> 18.2 15.21 1 49 1 0
#> 68 20.62 1 44 0 0
#> 25.1 6.32 1 34 1 0
#> 69.1 23.23 1 25 0 1
#> 158.3 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 15 22.68 1 48 0 0
#> 99.1 21.19 1 38 0 1
#> 26 15.77 1 49 0 1
#> 136 21.83 1 43 0 1
#> 190.1 20.81 1 42 1 0
#> 41 18.02 1 40 1 0
#> 127 3.53 1 62 0 1
#> 69.2 23.23 1 25 0 1
#> 6 15.64 1 39 0 0
#> 167 15.55 1 56 1 0
#> 107 11.18 1 54 1 0
#> 187 9.92 1 39 1 0
#> 29 15.45 1 68 1 0
#> 167.1 15.55 1 56 1 0
#> 32.1 20.90 1 37 1 0
#> 150.1 20.33 1 48 0 0
#> 6.1 15.64 1 39 0 0
#> 18.3 15.21 1 49 1 0
#> 194.1 22.40 1 38 0 1
#> 57 14.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 180 14.82 1 37 0 0
#> 18.4 15.21 1 49 1 0
#> 41.1 18.02 1 40 1 0
#> 101 9.97 1 10 0 1
#> 15.1 22.68 1 48 0 0
#> 10 10.53 1 34 0 0
#> 69.3 23.23 1 25 0 1
#> 76.1 19.22 1 54 0 1
#> 111 17.45 1 47 0 1
#> 18.5 15.21 1 49 1 0
#> 18.6 15.21 1 49 1 0
#> 86 23.81 1 58 0 1
#> 14.1 12.89 1 21 0 0
#> 199.1 19.81 1 NA 0 1
#> 88.1 18.37 1 47 0 0
#> 18.7 15.21 1 49 1 0
#> 4 17.64 1 NA 0 1
#> 195.1 11.76 1 NA 1 0
#> 91.1 5.33 1 61 0 1
#> 51 18.23 1 83 0 1
#> 166 19.98 1 48 0 0
#> 60.1 13.15 1 38 1 0
#> 40 18.00 1 28 1 0
#> 5 16.43 1 51 0 1
#> 197 21.60 1 69 1 0
#> 123 13.00 1 44 1 0
#> 91.2 5.33 1 61 0 1
#> 183.1 9.24 1 67 1 0
#> 110 17.56 1 65 0 1
#> 155 13.08 1 26 0 0
#> 169 22.41 1 46 0 0
#> 123.1 13.00 1 44 1 0
#> 138 24.00 0 44 1 0
#> 33 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 173 24.00 0 19 0 1
#> 17 24.00 0 38 0 1
#> 151 24.00 0 42 0 0
#> 95.1 24.00 0 68 0 1
#> 138.1 24.00 0 44 1 0
#> 173.1 24.00 0 19 0 1
#> 172 24.00 0 41 0 0
#> 82 24.00 0 34 0 0
#> 142 24.00 0 53 0 0
#> 53 24.00 0 32 0 1
#> 173.2 24.00 0 19 0 1
#> 122 24.00 0 66 0 0
#> 7 24.00 0 37 1 0
#> 27 24.00 0 63 1 0
#> 132 24.00 0 55 0 0
#> 122.1 24.00 0 66 0 0
#> 120 24.00 0 68 0 1
#> 3 24.00 0 31 1 0
#> 53.1 24.00 0 32 0 1
#> 174 24.00 0 49 1 0
#> 132.1 24.00 0 55 0 0
#> 33.1 24.00 0 53 0 0
#> 148 24.00 0 61 1 0
#> 87 24.00 0 27 0 0
#> 174.1 24.00 0 49 1 0
#> 83 24.00 0 6 0 0
#> 20 24.00 0 46 1 0
#> 163 24.00 0 66 0 0
#> 147 24.00 0 76 1 0
#> 178 24.00 0 52 1 0
#> 191 24.00 0 60 0 1
#> 7.1 24.00 0 37 1 0
#> 116 24.00 0 58 0 1
#> 75 24.00 0 21 1 0
#> 126 24.00 0 48 0 0
#> 163.1 24.00 0 66 0 0
#> 103 24.00 0 56 1 0
#> 142.1 24.00 0 53 0 0
#> 156 24.00 0 50 1 0
#> 84 24.00 0 39 0 1
#> 102 24.00 0 49 0 0
#> 83.1 24.00 0 6 0 0
#> 120.1 24.00 0 68 0 1
#> 87.1 24.00 0 27 0 0
#> 19 24.00 0 57 0 1
#> 144 24.00 0 28 0 1
#> 74 24.00 0 43 0 1
#> 94 24.00 0 51 0 1
#> 191.1 24.00 0 60 0 1
#> 112 24.00 0 61 0 0
#> 75.1 24.00 0 21 1 0
#> 112.1 24.00 0 61 0 0
#> 185 24.00 0 44 1 0
#> 21 24.00 0 47 0 0
#> 132.2 24.00 0 55 0 0
#> 64 24.00 0 43 0 0
#> 138.2 24.00 0 44 1 0
#> 20.1 24.00 0 46 1 0
#> 102.1 24.00 0 49 0 0
#> 34 24.00 0 36 0 0
#> 1 24.00 0 23 1 0
#> 28 24.00 0 67 1 0
#> 151.1 24.00 0 42 0 0
#> 33.2 24.00 0 53 0 0
#> 165 24.00 0 47 0 0
#> 200 24.00 0 64 0 0
#> 1.1 24.00 0 23 1 0
#> 87.2 24.00 0 27 0 0
#> 137 24.00 0 45 1 0
#> 31 24.00 0 36 0 1
#> 27.1 24.00 0 63 1 0
#> 7.2 24.00 0 37 1 0
#> 196 24.00 0 19 0 0
#> 73 24.00 0 NA 0 1
#> 161 24.00 0 45 0 0
#> 84.1 24.00 0 39 0 1
#> 9 24.00 0 31 1 0
#> 198 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 83.2 24.00 0 6 0 0
#> 135 24.00 0 58 1 0
#> 20.2 24.00 0 46 1 0
#> 131 24.00 0 66 0 0
#> 115 24.00 0 NA 1 0
#> 34.1 24.00 0 36 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.752 NA NA NA
#> 2 age, Cure model 0.0124 NA NA NA
#> 3 grade_ii, Cure model 0.558 NA NA NA
#> 4 grade_iii, Cure model 0.597 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00198 NA NA NA
#> 2 grade_ii, Survival model 0.446 NA NA NA
#> 3 grade_iii, Survival model -0.437 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.75163 0.01241 0.55758 0.59721
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262.9
#> Residual Deviance: 257.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.75163293 0.01240743 0.55758189 0.59720778
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.001975163 0.445923569 -0.437121692
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3223429793 0.4808318536 0.9446682444 0.6644832010 0.5421177302
#> [6] 0.0955975302 0.9629795141 0.2940673305 0.5830667254 0.9168243470
#> [11] 0.8321678586 0.5009740208 0.1285590093 0.3319641991 0.2000163317
#> [16] 0.2940673305 0.0052082792 0.1285590093 0.2292969668 0.3513935209
#> [21] 0.4606853350 0.2488856183 0.4408887286 0.1798169974 0.1481520887
#> [26] 0.1688445478 0.5318316470 0.8134197831 0.5627972455 0.6644832010
#> [31] 0.5009740208 0.3713626853 0.8510104710 0.2488856183 0.0650730491
#> [36] 0.5627972455 0.6036293613 0.8885794535 0.3613671140 0.8416100261
#> [41] 0.0848947912 0.3813747776 0.0126008467 0.4808318536 0.2488856183
#> [46] 0.3127430228 0.7470671481 0.5214617679 0.8604540708 0.6644832010
#> [51] 0.2193630102 0.9446682444 0.0126008467 0.2488856183 0.7662603592
#> [56] 0.0383854633 0.1481520887 0.5933111907 0.1063999206 0.2000163317
#> [61] 0.4113949139 0.9906512048 0.0126008467 0.6138829811 0.6342690809
#> [66] 0.8698542741 0.9074263756 0.6543975256 0.6342690809 0.1798169974
#> [71] 0.2292969668 0.6138829811 0.6644832010 0.0650730491 0.7566388602
#> [76] 0.9353845416 0.7375084779 0.6644832010 0.4113949139 0.8979847809
#> [81] 0.0383854633 0.8792136256 0.0126008467 0.3319641991 0.4707142540
#> [86] 0.6644832010 0.6644832010 0.0009176679 0.8134197831 0.3813747776
#> [91] 0.6644832010 0.9629795141 0.4012275269 0.2846444975 0.7662603592
#> [96] 0.4310532699 0.5524172320 0.1176681947 0.7946892662 0.9629795141
#> [101] 0.9168243470 0.4507400867 0.7851706968 0.0555543739 0.7946892662
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 58 30 25 18 85 175 91 105 100 183 177 45 153
#> 19.34 17.43 6.32 15.21 16.44 21.91 5.33 19.75 16.07 9.24 12.53 17.42 21.33
#> 76 190 105.1 164 153.1 150 97 117 158 184 32 99 90
#> 19.22 20.81 19.75 23.60 21.33 20.33 19.14 17.46 20.14 17.77 20.90 21.19 20.94
#> 106 14 79 18.1 45.1 8 42 158.1 194 79.1 125 61 179
#> 16.67 12.89 16.23 15.21 17.42 18.43 12.43 20.14 22.40 16.23 15.65 10.12 18.63
#> 37 66 88 69 30.1 158.2 170 133 23 49 18.2 68 25.1
#> 12.52 22.13 18.37 23.23 17.43 20.14 19.54 14.65 16.92 12.19 15.21 20.62 6.32
#> 69.1 158.3 60 15 99.1 26 136 190.1 41 127 69.2 6 167
#> 23.23 20.14 13.15 22.68 21.19 15.77 21.83 20.81 18.02 3.53 23.23 15.64 15.55
#> 107 187 29 167.1 32.1 150.1 6.1 18.3 194.1 57 149 180 18.4
#> 11.18 9.92 15.45 15.55 20.90 20.33 15.64 15.21 22.40 14.46 8.37 14.82 15.21
#> 41.1 101 15.1 10 69.3 76.1 111 18.5 18.6 86 14.1 88.1 18.7
#> 18.02 9.97 22.68 10.53 23.23 19.22 17.45 15.21 15.21 23.81 12.89 18.37 15.21
#> 91.1 51 166 60.1 40 5 197 123 91.2 183.1 110 155 169
#> 5.33 18.23 19.98 13.15 18.00 16.43 21.60 13.00 5.33 9.24 17.56 13.08 22.41
#> 123.1 138 33 95 173 17 151 95.1 138.1 173.1 172 82 142
#> 13.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53 173.2 122 7 27 132 122.1 120 3 53.1 174 132.1 33.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148 87 174.1 83 20 163 147 178 191 7.1 116 75 126
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.1 103 142.1 156 84 102 83.1 120.1 87.1 19 144 74 94
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 191.1 112 75.1 112.1 185 21 132.2 64 138.2 20.1 102.1 34 1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28 151.1 33.2 165 200 1.1 87.2 137 31 27.1 7.2 196 161
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 84.1 9 198 12 83.2 135 20.2 131 34.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[95]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.00385805 0.73159511 0.29847344
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.584966916 0.007742433 0.111886777
#> grade_iii, Cure model
#> 1.108402253
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 145 10.07 1 65 1 0
#> 5 16.43 1 51 0 1
#> 4 17.64 1 NA 0 1
#> 79 16.23 1 54 1 0
#> 184 17.77 1 38 0 0
#> 77 7.27 1 67 0 1
#> 107 11.18 1 54 1 0
#> 125 15.65 1 67 1 0
#> 113 22.86 1 34 0 0
#> 79.1 16.23 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 125.1 15.65 1 67 1 0
#> 134 17.81 1 47 1 0
#> 150 20.33 1 48 0 0
#> 133 14.65 1 57 0 0
#> 90 20.94 1 50 0 1
#> 110 17.56 1 65 0 1
#> 171 16.57 1 41 0 1
#> 30 17.43 1 78 0 0
#> 99 21.19 1 38 0 1
#> 86 23.81 1 58 0 1
#> 41 18.02 1 40 1 0
#> 13 14.34 1 54 0 1
#> 130 16.47 1 53 0 1
#> 13.1 14.34 1 54 0 1
#> 29 15.45 1 68 1 0
#> 32 20.90 1 37 1 0
#> 69 23.23 1 25 0 1
#> 15 22.68 1 48 0 0
#> 57 14.46 1 45 0 1
#> 166 19.98 1 48 0 0
#> 89.1 11.44 1 NA 0 0
#> 99.1 21.19 1 38 0 1
#> 159 10.55 1 50 0 1
#> 183 9.24 1 67 1 0
#> 158 20.14 1 74 1 0
#> 134.1 17.81 1 47 1 0
#> 96 14.54 1 33 0 1
#> 187 9.92 1 39 1 0
#> 59 10.16 1 NA 1 0
#> 79.2 16.23 1 54 1 0
#> 57.1 14.46 1 45 0 1
#> 59.1 10.16 1 NA 1 0
#> 8 18.43 1 32 0 0
#> 108 18.29 1 39 0 1
#> 60 13.15 1 38 1 0
#> 117 17.46 1 26 0 1
#> 5.1 16.43 1 51 0 1
#> 92 22.92 1 47 0 1
#> 79.3 16.23 1 54 1 0
#> 114 13.68 1 NA 0 0
#> 66 22.13 1 53 0 0
#> 127 3.53 1 62 0 1
#> 88 18.37 1 47 0 0
#> 117.1 17.46 1 26 0 1
#> 14 12.89 1 21 0 0
#> 133.1 14.65 1 57 0 0
#> 16 8.71 1 71 0 1
#> 175 21.91 1 43 0 0
#> 23 16.92 1 61 0 0
#> 181 16.46 1 45 0 1
#> 149 8.37 1 33 1 0
#> 81 14.06 1 34 0 0
#> 43 12.10 1 61 0 1
#> 45 17.42 1 54 0 1
#> 177 12.53 1 75 0 0
#> 158.1 20.14 1 74 1 0
#> 125.2 15.65 1 67 1 0
#> 40 18.00 1 28 1 0
#> 49 12.19 1 48 1 0
#> 157 15.10 1 47 0 0
#> 39 15.59 1 37 0 1
#> 76 19.22 1 54 0 1
#> 117.2 17.46 1 26 0 1
#> 188 16.16 1 46 0 1
#> 190 20.81 1 42 1 0
#> 78 23.88 1 43 0 0
#> 181.1 16.46 1 45 0 1
#> 88.1 18.37 1 47 0 0
#> 189 10.51 1 NA 1 0
#> 150.1 20.33 1 48 0 0
#> 177.1 12.53 1 75 0 0
#> 101 9.97 1 10 0 1
#> 93 10.33 1 52 0 1
#> 36 21.19 1 48 0 1
#> 26 15.77 1 49 0 1
#> 36.1 21.19 1 48 0 1
#> 169 22.41 1 46 0 0
#> 32.1 20.90 1 37 1 0
#> 51 18.23 1 83 0 1
#> 23.1 16.92 1 61 0 0
#> 90.1 20.94 1 50 0 1
#> 167 15.55 1 56 1 0
#> 180 14.82 1 37 0 0
#> 25 6.32 1 34 1 0
#> 15.1 22.68 1 48 0 0
#> 77.1 7.27 1 67 0 1
#> 114.1 13.68 1 NA 0 0
#> 155 13.08 1 26 0 0
#> 79.4 16.23 1 54 1 0
#> 61 10.12 1 36 0 1
#> 8.1 18.43 1 32 0 0
#> 70 7.38 1 30 1 0
#> 66.1 22.13 1 53 0 0
#> 79.5 16.23 1 54 1 0
#> 32.2 20.90 1 37 1 0
#> 164 23.60 1 76 0 1
#> 97 19.14 1 65 0 1
#> 113.1 22.86 1 34 0 0
#> 127.1 3.53 1 62 0 1
#> 55 19.34 1 69 0 1
#> 6 15.64 1 39 0 0
#> 116 24.00 0 58 0 1
#> 44 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 98 24.00 0 34 1 0
#> 65 24.00 0 57 1 0
#> 142.1 24.00 0 53 0 0
#> 104 24.00 0 50 1 0
#> 33 24.00 0 53 0 0
#> 64 24.00 0 43 0 0
#> 186 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#> 64.1 24.00 0 43 0 0
#> 64.2 24.00 0 43 0 0
#> 156 24.00 0 50 1 0
#> 75 24.00 0 21 1 0
#> 163 24.00 0 66 0 0
#> 162 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 160 24.00 0 31 1 0
#> 174 24.00 0 49 1 0
#> 163.2 24.00 0 66 0 0
#> 176 24.00 0 43 0 1
#> 67 24.00 0 25 0 0
#> 120 24.00 0 68 0 1
#> 116.1 24.00 0 58 0 1
#> 200 24.00 0 64 0 0
#> 156.1 24.00 0 50 1 0
#> 148 24.00 0 61 1 0
#> 160.1 24.00 0 31 1 0
#> 28 24.00 0 67 1 0
#> 121 24.00 0 57 1 0
#> 182 24.00 0 35 0 0
#> 146 24.00 0 63 1 0
#> 112 24.00 0 61 0 0
#> 103 24.00 0 56 1 0
#> 144.1 24.00 0 28 0 1
#> 82 24.00 0 34 0 0
#> 84 24.00 0 39 0 1
#> 38 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 132 24.00 0 55 0 0
#> 74 24.00 0 43 0 1
#> 172 24.00 0 41 0 0
#> 122 24.00 0 66 0 0
#> 185 24.00 0 44 1 0
#> 146.1 24.00 0 63 1 0
#> 200.1 24.00 0 64 0 0
#> 27 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 138 24.00 0 44 1 0
#> 198 24.00 0 66 0 1
#> 12 24.00 0 63 0 0
#> 138.1 24.00 0 44 1 0
#> 131 24.00 0 66 0 0
#> 131.1 24.00 0 66 0 0
#> 33.1 24.00 0 53 0 0
#> 121.1 24.00 0 57 1 0
#> 53 24.00 0 32 0 1
#> 33.2 24.00 0 53 0 0
#> 156.2 24.00 0 50 1 0
#> 122.1 24.00 0 66 0 0
#> 152 24.00 0 36 0 1
#> 143 24.00 0 51 0 0
#> 65.1 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 196 24.00 0 19 0 0
#> 65.2 24.00 0 57 1 0
#> 122.2 24.00 0 66 0 0
#> 196.1 24.00 0 19 0 0
#> 173 24.00 0 19 0 1
#> 20 24.00 0 46 1 0
#> 87 24.00 0 27 0 0
#> 98.1 24.00 0 34 1 0
#> 44.1 24.00 0 56 0 0
#> 19 24.00 0 57 0 1
#> 193 24.00 0 45 0 1
#> 152.1 24.00 0 36 0 1
#> 182.1 24.00 0 35 0 0
#> 160.2 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 165 24.00 0 47 0 0
#> 3 24.00 0 31 1 0
#> 19.1 24.00 0 57 0 1
#> 11 24.00 0 42 0 1
#> 121.2 24.00 0 57 1 0
#> 137.1 24.00 0 45 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.585 NA NA NA
#> 2 age, Cure model 0.00774 NA NA NA
#> 3 grade_ii, Cure model 0.112 NA NA NA
#> 4 grade_iii, Cure model 1.11 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00386 NA NA NA
#> 2 grade_ii, Survival model 0.732 NA NA NA
#> 3 grade_iii, Survival model 0.298 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.584967 0.007742 0.111887 1.108402
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 264.8
#> Residual Deviance: 253.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.584966916 0.007742433 0.111886777 1.108402253
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.00385805 0.73159511 0.29847344
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.93293599 0.68918153 0.70444847 0.58469508 0.97271607 0.90938446
#> [7] 0.75901281 0.15589500 0.70444847 0.75901281 0.56790867 0.41262316
#> [13] 0.81717037 0.34136740 0.59313015 0.65783585 0.62568990 0.28825799
#> [19] 0.06637132 0.55002207 0.84848522 0.66579616 0.84848522 0.79811209
#> [25] 0.36769157 0.11652842 0.19020751 0.83605630 0.45432325 0.28825799
#> [31] 0.91530777 0.95023868 0.43435468 0.56790867 0.82976191 0.94450898
#> [37] 0.70444847 0.83605630 0.49362996 0.53137625 0.86696604 0.60147833
#> [43] 0.68918153 0.13707625 0.70444847 0.24029258 0.98917678 0.51257213
#> [49] 0.60147833 0.87918102 0.81717037 0.95591054 0.27205804 0.64190064
#> [55] 0.67369475 0.96155652 0.86079513 0.90340035 0.63382947 0.88528268
#> [61] 0.43435468 0.75901281 0.55905946 0.89738815 0.80447405 0.78512910
#> [67] 0.47426292 0.60147833 0.74522010 0.40148968 0.02844951 0.67369475
#> [73] 0.51257213 0.41262316 0.88528268 0.93872963 0.92120686 0.28825799
#> [79] 0.75213632 0.28825799 0.22332374 0.36769157 0.54076798 0.64190064
#> [85] 0.34136740 0.79166263 0.81082602 0.98370757 0.19020751 0.97271607
#> [91] 0.87307579 0.70444847 0.92708160 0.49362996 0.96715776 0.24029258
#> [97] 0.70444847 0.36769157 0.09408069 0.48401734 0.15589500 0.98917678
#> [103] 0.46437429 0.77856528 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 145 5 79 184 77 107 125 113 79.1 125.1 134 150 133
#> 10.07 16.43 16.23 17.77 7.27 11.18 15.65 22.86 16.23 15.65 17.81 20.33 14.65
#> 90 110 171 30 99 86 41 13 130 13.1 29 32 69
#> 20.94 17.56 16.57 17.43 21.19 23.81 18.02 14.34 16.47 14.34 15.45 20.90 23.23
#> 15 57 166 99.1 159 183 158 134.1 96 187 79.2 57.1 8
#> 22.68 14.46 19.98 21.19 10.55 9.24 20.14 17.81 14.54 9.92 16.23 14.46 18.43
#> 108 60 117 5.1 92 79.3 66 127 88 117.1 14 133.1 16
#> 18.29 13.15 17.46 16.43 22.92 16.23 22.13 3.53 18.37 17.46 12.89 14.65 8.71
#> 175 23 181 149 81 43 45 177 158.1 125.2 40 49 157
#> 21.91 16.92 16.46 8.37 14.06 12.10 17.42 12.53 20.14 15.65 18.00 12.19 15.10
#> 39 76 117.2 188 190 78 181.1 88.1 150.1 177.1 101 93 36
#> 15.59 19.22 17.46 16.16 20.81 23.88 16.46 18.37 20.33 12.53 9.97 10.33 21.19
#> 26 36.1 169 32.1 51 23.1 90.1 167 180 25 15.1 77.1 155
#> 15.77 21.19 22.41 20.90 18.23 16.92 20.94 15.55 14.82 6.32 22.68 7.27 13.08
#> 79.4 61 8.1 70 66.1 79.5 32.2 164 97 113.1 127.1 55 6
#> 16.23 10.12 18.43 7.38 22.13 16.23 20.90 23.60 19.14 22.86 3.53 19.34 15.64
#> 116 44 142 98 65 142.1 104 33 64 186 48 144 64.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 64.2 156 75 163 162 163.1 160 174 163.2 176 67 120 116.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 200 156.1 148 160.1 28 121 182 146 112 103 144.1 82 84
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 38 137 132 74 172 122 185 146.1 200.1 27 35 83 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 198 12 138.1 131 131.1 33.1 121.1 53 33.2 156.2 122.1 152 143
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 65.1 102 196 65.2 122.2 196.1 173 20 87 98.1 44.1 19 193
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 152.1 182.1 160.2 191 165 3 19.1 11 121.2 137.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[96]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.002820142 0.491720951 0.316138756
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.40715528 0.01036635 -0.36477484
#> grade_iii, Cure model
#> 0.69912339
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 29 15.45 1 68 1 0
#> 86 23.81 1 58 0 1
#> 92 22.92 1 47 0 1
#> 61 10.12 1 36 0 1
#> 108 18.29 1 39 0 1
#> 129 23.41 1 53 1 0
#> 101 9.97 1 10 0 1
#> 187 9.92 1 39 1 0
#> 85 16.44 1 36 0 0
#> 68 20.62 1 44 0 0
#> 43 12.10 1 61 0 1
#> 145 10.07 1 65 1 0
#> 85.1 16.44 1 36 0 0
#> 45 17.42 1 54 0 1
#> 51 18.23 1 83 0 1
#> 177 12.53 1 75 0 0
#> 130 16.47 1 53 0 1
#> 164 23.60 1 76 0 1
#> 23 16.92 1 61 0 0
#> 177.1 12.53 1 75 0 0
#> 177.2 12.53 1 75 0 0
#> 76 19.22 1 54 0 1
#> 111 17.45 1 47 0 1
#> 179 18.63 1 42 0 0
#> 177.3 12.53 1 75 0 0
#> 154 12.63 1 20 1 0
#> 24 23.89 1 38 0 0
#> 124 9.73 1 NA 1 0
#> 128 20.35 1 35 0 1
#> 153 21.33 1 55 1 0
#> 85.2 16.44 1 36 0 0
#> 170 19.54 1 43 0 1
#> 127 3.53 1 62 0 1
#> 108.1 18.29 1 39 0 1
#> 30 17.43 1 78 0 0
#> 113 22.86 1 34 0 0
#> 177.4 12.53 1 75 0 0
#> 110 17.56 1 65 0 1
#> 158 20.14 1 74 1 0
#> 50 10.02 1 NA 1 0
#> 117 17.46 1 26 0 1
#> 61.1 10.12 1 36 0 1
#> 93 10.33 1 52 0 1
#> 49 12.19 1 48 1 0
#> 158.1 20.14 1 74 1 0
#> 96 14.54 1 33 0 1
#> 134 17.81 1 47 1 0
#> 180 14.82 1 37 0 0
#> 90 20.94 1 50 0 1
#> 8 18.43 1 32 0 0
#> 51.1 18.23 1 83 0 1
#> 139 21.49 1 63 1 0
#> 111.1 17.45 1 47 0 1
#> 134.1 17.81 1 47 1 0
#> 199 19.81 1 NA 0 1
#> 90.1 20.94 1 50 0 1
#> 171 16.57 1 41 0 1
#> 150 20.33 1 48 0 0
#> 123 13.00 1 44 1 0
#> 36 21.19 1 48 0 1
#> 136 21.83 1 43 0 1
#> 127.1 3.53 1 62 0 1
#> 43.1 12.10 1 61 0 1
#> 61.2 10.12 1 36 0 1
#> 23.1 16.92 1 61 0 0
#> 79 16.23 1 54 1 0
#> 157 15.10 1 47 0 0
#> 97 19.14 1 65 0 1
#> 192 16.44 1 31 1 0
#> 51.2 18.23 1 83 0 1
#> 68.1 20.62 1 44 0 0
#> 13 14.34 1 54 0 1
#> 169 22.41 1 46 0 0
#> 179.1 18.63 1 42 0 0
#> 129.1 23.41 1 53 1 0
#> 13.1 14.34 1 54 0 1
#> 60 13.15 1 38 1 0
#> 60.1 13.15 1 38 1 0
#> 175 21.91 1 43 0 0
#> 157.1 15.10 1 47 0 0
#> 114 13.68 1 NA 0 0
#> 168 23.72 1 70 0 0
#> 36.1 21.19 1 48 0 1
#> 170.1 19.54 1 43 0 1
#> 140 12.68 1 59 1 0
#> 183 9.24 1 67 1 0
#> 58 19.34 1 39 0 0
#> 85.3 16.44 1 36 0 0
#> 157.2 15.10 1 47 0 0
#> 66 22.13 1 53 0 0
#> 37 12.52 1 57 1 0
#> 77 7.27 1 67 0 1
#> 78 23.88 1 43 0 0
#> 177.5 12.53 1 75 0 0
#> 29.1 15.45 1 68 1 0
#> 41 18.02 1 40 1 0
#> 45.1 17.42 1 54 0 1
#> 99 21.19 1 38 0 1
#> 89 11.44 1 NA 0 0
#> 97.1 19.14 1 65 0 1
#> 179.2 18.63 1 42 0 0
#> 42 12.43 1 49 0 1
#> 166 19.98 1 48 0 0
#> 159 10.55 1 50 0 1
#> 133 14.65 1 57 0 0
#> 117.1 17.46 1 26 0 1
#> 106 16.67 1 49 1 0
#> 140.1 12.68 1 59 1 0
#> 101.1 9.97 1 10 0 1
#> 55 19.34 1 69 0 1
#> 187.1 9.92 1 39 1 0
#> 43.2 12.10 1 61 0 1
#> 165 24.00 0 47 0 0
#> 160 24.00 0 31 1 0
#> 147 24.00 0 76 1 0
#> 118 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 147.1 24.00 0 76 1 0
#> 126 24.00 0 48 0 0
#> 94 24.00 0 51 0 1
#> 34 24.00 0 36 0 0
#> 38 24.00 0 31 1 0
#> 165.1 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 80 24.00 0 41 0 0
#> 84 24.00 0 39 0 1
#> 19 24.00 0 57 0 1
#> 126.1 24.00 0 48 0 0
#> 46.1 24.00 0 71 0 0
#> 19.1 24.00 0 57 0 1
#> 27 24.00 0 63 1 0
#> 146 24.00 0 63 1 0
#> 172 24.00 0 41 0 0
#> 84.1 24.00 0 39 0 1
#> 84.2 24.00 0 39 0 1
#> 17 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 1 24.00 0 23 1 0
#> 82 24.00 0 34 0 0
#> 193 24.00 0 45 0 1
#> 193.1 24.00 0 45 0 1
#> 72 24.00 0 40 0 1
#> 1.1 24.00 0 23 1 0
#> 144 24.00 0 28 0 1
#> 34.1 24.00 0 36 0 0
#> 9 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 137 24.00 0 45 1 0
#> 165.2 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 7 24.00 0 37 1 0
#> 198 24.00 0 66 0 1
#> 198.1 24.00 0 66 0 1
#> 148 24.00 0 61 1 0
#> 160.1 24.00 0 31 1 0
#> 82.1 24.00 0 34 0 0
#> 109 24.00 0 48 0 0
#> 44.1 24.00 0 56 0 0
#> 19.2 24.00 0 57 0 1
#> 104 24.00 0 50 1 0
#> 62.1 24.00 0 71 0 0
#> 148.1 24.00 0 61 1 0
#> 163 24.00 0 66 0 0
#> 116 24.00 0 58 0 1
#> 138 24.00 0 44 1 0
#> 73 24.00 0 NA 0 1
#> 137.1 24.00 0 45 1 0
#> 74 24.00 0 43 0 1
#> 54 24.00 0 53 1 0
#> 28 24.00 0 67 1 0
#> 9.1 24.00 0 31 1 0
#> 193.2 24.00 0 45 0 1
#> 62.2 24.00 0 71 0 0
#> 33 24.00 0 53 0 0
#> 165.3 24.00 0 47 0 0
#> 28.1 24.00 0 67 1 0
#> 71 24.00 0 51 0 0
#> 118.1 24.00 0 44 1 0
#> 156 24.00 0 50 1 0
#> 131 24.00 0 66 0 0
#> 65 24.00 0 57 1 0
#> 102 24.00 0 49 0 0
#> 11 24.00 0 42 0 1
#> 172.1 24.00 0 41 0 0
#> 28.2 24.00 0 67 1 0
#> 162 24.00 0 51 0 0
#> 38.1 24.00 0 31 1 0
#> 118.2 24.00 0 44 1 0
#> 95 24.00 0 68 0 1
#> 185 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 64 24.00 0 43 0 0
#> 165.4 24.00 0 47 0 0
#> 1.2 24.00 0 23 1 0
#> 75 24.00 0 21 1 0
#> 115.1 24.00 0 NA 1 0
#> 94.1 24.00 0 51 0 1
#> 116.1 24.00 0 58 0 1
#> 122 24.00 0 66 0 0
#> 118.3 24.00 0 44 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.407 NA NA NA
#> 2 age, Cure model 0.0104 NA NA NA
#> 3 grade_ii, Cure model -0.365 NA NA NA
#> 4 grade_iii, Cure model 0.699 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.00282 NA NA NA
#> 2 grade_ii, Survival model 0.492 NA NA NA
#> 3 grade_iii, Survival model 0.316 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.40716 0.01037 -0.36477 0.69912
#>
#> Degrees of Freedom: 191 Total (i.e. Null); 188 Residual
#> Null Deviance: 263.6
#> Residual Deviance: 253.7 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.40715528 0.01036635 -0.36477484 0.69912339
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.002820142 0.491720951 0.316138756
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.645646256 0.031563182 0.091960806 0.901473727 0.402901926 0.070908806
#> [7] 0.934611930 0.951081426 0.593661678 0.229570924 0.859581791 0.926291445
#> [13] 0.593661678 0.531133871 0.421730571 0.783979257 0.584752750 0.057763182
#> [19] 0.548948321 0.783979257 0.783979257 0.336669779 0.504238055 0.365137172
#> [25] 0.783979257 0.775506997 0.005920317 0.249357380 0.170103681 0.593661678
#> [31] 0.298506377 0.983768650 0.402901926 0.522096280 0.102903113 0.783979257
#> [37] 0.477079453 0.269405268 0.486251535 0.901473727 0.893068161 0.851105166
#> [43] 0.269405268 0.706614834 0.458862371 0.689017093 0.209982404 0.393270778
#> [49] 0.421730571 0.159142206 0.504238055 0.458862371 0.209982404 0.575819140
#> [55] 0.259356779 0.749956177 0.180789897 0.147895342 0.983768650 0.859581791
#> [61] 0.901473727 0.548948321 0.636820265 0.663012679 0.346296938 0.593661678
#> [67] 0.421730571 0.229570924 0.715394597 0.113953880 0.365137172 0.070908806
#> [73] 0.715394597 0.732770928 0.732770928 0.136461925 0.663012679 0.044304636
#> [79] 0.180789897 0.298506377 0.758554575 0.967419424 0.317595095 0.593661678
#> [85] 0.663012679 0.125137353 0.834062539 0.975598682 0.018020469 0.783979257
#> [91] 0.645646256 0.449499379 0.531133871 0.180789897 0.346296938 0.365137172
#> [97] 0.842592245 0.288666968 0.884647957 0.697807726 0.486251535 0.566854654
#> [103] 0.758554575 0.934611930 0.317595095 0.951081426 0.859581791 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 29 86 92 61 108 129 101 187 85 68 43 145 85.1
#> 15.45 23.81 22.92 10.12 18.29 23.41 9.97 9.92 16.44 20.62 12.10 10.07 16.44
#> 45 51 177 130 164 23 177.1 177.2 76 111 179 177.3 154
#> 17.42 18.23 12.53 16.47 23.60 16.92 12.53 12.53 19.22 17.45 18.63 12.53 12.63
#> 24 128 153 85.2 170 127 108.1 30 113 177.4 110 158 117
#> 23.89 20.35 21.33 16.44 19.54 3.53 18.29 17.43 22.86 12.53 17.56 20.14 17.46
#> 61.1 93 49 158.1 96 134 180 90 8 51.1 139 111.1 134.1
#> 10.12 10.33 12.19 20.14 14.54 17.81 14.82 20.94 18.43 18.23 21.49 17.45 17.81
#> 90.1 171 150 123 36 136 127.1 43.1 61.2 23.1 79 157 97
#> 20.94 16.57 20.33 13.00 21.19 21.83 3.53 12.10 10.12 16.92 16.23 15.10 19.14
#> 192 51.2 68.1 13 169 179.1 129.1 13.1 60 60.1 175 157.1 168
#> 16.44 18.23 20.62 14.34 22.41 18.63 23.41 14.34 13.15 13.15 21.91 15.10 23.72
#> 36.1 170.1 140 183 58 85.3 157.2 66 37 77 78 177.5 29.1
#> 21.19 19.54 12.68 9.24 19.34 16.44 15.10 22.13 12.52 7.27 23.88 12.53 15.45
#> 41 45.1 99 97.1 179.2 42 166 159 133 117.1 106 140.1 101.1
#> 18.02 17.42 21.19 19.14 18.63 12.43 19.98 10.55 14.65 17.46 16.67 12.68 9.97
#> 55 187.1 43.2 165 160 147 118 44 147.1 126 94 34 38
#> 19.34 9.92 12.10 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.1 46 80 84 19 126.1 46.1 19.1 27 146 172 84.1 84.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 186 1 82 193 193.1 72 1.1 144 34.1 9 98 137
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 165.2 62 7 198 198.1 148 160.1 82.1 109 44.1 19.2 104 62.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 148.1 163 116 138 137.1 74 54 28 9.1 193.2 62.2 33 165.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 28.1 71 118.1 156 131 65 102 11 172.1 28.2 162 38.1 118.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 95 185 64 165.4 1.2 75 94.1 116.1 122 118.3
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[97]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> 0.003708756 0.198924136 0.204613063
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.543262569 0.009818745 -0.240717945
#> grade_iii, Cure model
#> 0.917130747
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 155 13.08 1 26 0 0
#> 81 14.06 1 34 0 0
#> 90 20.94 1 50 0 1
#> 114 13.68 1 NA 0 0
#> 26 15.77 1 49 0 1
#> 124 9.73 1 NA 1 0
#> 55 19.34 1 69 0 1
#> 100 16.07 1 60 0 0
#> 79 16.23 1 54 1 0
#> 105 19.75 1 60 0 0
#> 36 21.19 1 48 0 1
#> 128 20.35 1 35 0 1
#> 4 17.64 1 NA 0 1
#> 79.1 16.23 1 54 1 0
#> 68 20.62 1 44 0 0
#> 190 20.81 1 42 1 0
#> 170 19.54 1 43 0 1
#> 189 10.51 1 NA 1 0
#> 63 22.77 1 31 1 0
#> 39 15.59 1 37 0 1
#> 92 22.92 1 47 0 1
#> 76 19.22 1 54 0 1
#> 97 19.14 1 65 0 1
#> 128.1 20.35 1 35 0 1
#> 41 18.02 1 40 1 0
#> 177 12.53 1 75 0 0
#> 133 14.65 1 57 0 0
#> 192 16.44 1 31 1 0
#> 77 7.27 1 67 0 1
#> 113 22.86 1 34 0 0
#> 58 19.34 1 39 0 0
#> 97.1 19.14 1 65 0 1
#> 89 11.44 1 NA 0 0
#> 69 23.23 1 25 0 1
#> 14 12.89 1 21 0 0
#> 153 21.33 1 55 1 0
#> 155.1 13.08 1 26 0 0
#> 61 10.12 1 36 0 1
#> 159 10.55 1 50 0 1
#> 76.1 19.22 1 54 0 1
#> 167 15.55 1 56 1 0
#> 8 18.43 1 32 0 0
#> 114.1 13.68 1 NA 0 0
#> 68.1 20.62 1 44 0 0
#> 99 21.19 1 38 0 1
#> 36.1 21.19 1 48 0 1
#> 69.1 23.23 1 25 0 1
#> 183 9.24 1 67 1 0
#> 69.2 23.23 1 25 0 1
#> 197 21.60 1 69 1 0
#> 168 23.72 1 70 0 0
#> 110 17.56 1 65 0 1
#> 149 8.37 1 33 1 0
#> 77.1 7.27 1 67 0 1
#> 42 12.43 1 49 0 1
#> 140 12.68 1 59 1 0
#> 30 17.43 1 78 0 0
#> 159.1 10.55 1 50 0 1
#> 79.2 16.23 1 54 1 0
#> 169 22.41 1 46 0 0
#> 97.2 19.14 1 65 0 1
#> 4.1 17.64 1 NA 0 1
#> 129 23.41 1 53 1 0
#> 37 12.52 1 57 1 0
#> 184 17.77 1 38 0 0
#> 150 20.33 1 48 0 0
#> 92.1 22.92 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 51 18.23 1 83 0 1
#> 111 17.45 1 47 0 1
#> 188 16.16 1 46 0 1
#> 113.1 22.86 1 34 0 0
#> 106 16.67 1 49 1 0
#> 57 14.46 1 45 0 1
#> 8.1 18.43 1 32 0 0
#> 51.1 18.23 1 83 0 1
#> 145 10.07 1 65 1 0
#> 66 22.13 1 53 0 0
#> 166 19.98 1 48 0 0
#> 97.3 19.14 1 65 0 1
#> 188.1 16.16 1 46 0 1
#> 66.1 22.13 1 53 0 0
#> 39.1 15.59 1 37 0 1
#> 190.1 20.81 1 42 1 0
#> 188.2 16.16 1 46 0 1
#> 192.1 16.44 1 31 1 0
#> 55.1 19.34 1 69 0 1
#> 97.4 19.14 1 65 0 1
#> 179 18.63 1 42 0 0
#> 4.2 17.64 1 NA 0 1
#> 155.2 13.08 1 26 0 0
#> 133.1 14.65 1 57 0 0
#> 171 16.57 1 41 0 1
#> 93 10.33 1 52 0 1
#> 37.1 12.52 1 57 1 0
#> 13 14.34 1 54 0 1
#> 150.1 20.33 1 48 0 0
#> 192.2 16.44 1 31 1 0
#> 57.1 14.46 1 45 0 1
#> 170.1 19.54 1 43 0 1
#> 93.1 10.33 1 52 0 1
#> 129.1 23.41 1 53 1 0
#> 99.1 21.19 1 38 0 1
#> 168.1 23.72 1 70 0 0
#> 8.2 18.43 1 32 0 0
#> 179.1 18.63 1 42 0 0
#> 36.2 21.19 1 48 0 1
#> 171.1 16.57 1 41 0 1
#> 188.3 16.16 1 46 0 1
#> 184.1 17.77 1 38 0 0
#> 76.2 19.22 1 54 0 1
#> 46 24.00 0 71 0 0
#> 75 24.00 0 21 1 0
#> 119 24.00 0 17 0 0
#> 198 24.00 0 66 0 1
#> 142 24.00 0 53 0 0
#> 116 24.00 0 58 0 1
#> 22 24.00 0 52 1 0
#> 122 24.00 0 66 0 0
#> 54 24.00 0 53 1 0
#> 143 24.00 0 51 0 0
#> 31 24.00 0 36 0 1
#> 156 24.00 0 50 1 0
#> 176 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 196 24.00 0 19 0 0
#> 94 24.00 0 51 0 1
#> 131 24.00 0 66 0 0
#> 112 24.00 0 61 0 0
#> 83 24.00 0 6 0 0
#> 102 24.00 0 49 0 0
#> 2 24.00 0 9 0 0
#> 156.1 24.00 0 50 1 0
#> 22.1 24.00 0 52 1 0
#> 196.1 24.00 0 19 0 0
#> 17 24.00 0 38 0 1
#> 163 24.00 0 66 0 0
#> 98 24.00 0 34 1 0
#> 94.1 24.00 0 51 0 1
#> 75.1 24.00 0 21 1 0
#> 7 24.00 0 37 1 0
#> 198.1 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 31.1 24.00 0 36 0 1
#> 102.1 24.00 0 49 0 0
#> 71 24.00 0 51 0 0
#> 62 24.00 0 71 0 0
#> 74 24.00 0 43 0 1
#> 144 24.00 0 28 0 1
#> 131.1 24.00 0 66 0 0
#> 22.2 24.00 0 52 1 0
#> 120 24.00 0 68 0 1
#> 64 24.00 0 43 0 0
#> 148 24.00 0 61 1 0
#> 132 24.00 0 55 0 0
#> 115 24.00 0 NA 1 0
#> 35 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 28 24.00 0 67 1 0
#> 22.3 24.00 0 52 1 0
#> 64.1 24.00 0 43 0 0
#> 173 24.00 0 19 0 1
#> 9 24.00 0 31 1 0
#> 152 24.00 0 36 0 1
#> 22.4 24.00 0 52 1 0
#> 7.1 24.00 0 37 1 0
#> 156.2 24.00 0 50 1 0
#> 3 24.00 0 31 1 0
#> 121 24.00 0 57 1 0
#> 74.1 24.00 0 43 0 1
#> 146 24.00 0 63 1 0
#> 98.1 24.00 0 34 1 0
#> 21 24.00 0 47 0 0
#> 118 24.00 0 44 1 0
#> 21.1 24.00 0 47 0 0
#> 84 24.00 0 39 0 1
#> 193 24.00 0 45 0 1
#> 64.2 24.00 0 43 0 0
#> 163.2 24.00 0 66 0 0
#> 132.1 24.00 0 55 0 0
#> 17.1 24.00 0 38 0 1
#> 186 24.00 0 45 1 0
#> 3.1 24.00 0 31 1 0
#> 115.1 24.00 0 NA 1 0
#> 11 24.00 0 42 0 1
#> 132.2 24.00 0 55 0 0
#> 67 24.00 0 25 0 0
#> 161 24.00 0 45 0 0
#> 34 24.00 0 36 0 0
#> 53 24.00 0 32 0 1
#> 95 24.00 0 68 0 1
#> 87 24.00 0 27 0 0
#> 147 24.00 0 76 1 0
#> 132.3 24.00 0 55 0 0
#> 174 24.00 0 49 1 0
#> 148.1 24.00 0 61 1 0
#> 109 24.00 0 48 0 0
#> 87.1 24.00 0 27 0 0
#> 103 24.00 0 56 1 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.543 NA NA NA
#> 2 age, Cure model 0.00982 NA NA NA
#> 3 grade_ii, Cure model -0.241 NA NA NA
#> 4 grade_iii, Cure model 0.917 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model 0.00371 NA NA NA
#> 2 grade_ii, Survival model 0.199 NA NA NA
#> 3 grade_iii, Survival model 0.205 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.543263 0.009819 -0.240718 0.917131
#>
#> Degrees of Freedom: 188 Total (i.e. Null); 185 Residual
#> Null Deviance: 260.5
#> Residual Deviance: 248.3 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.543262569 0.009818745 -0.240717945 0.917130747
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> 0.003708756 0.198924136 0.204613063
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.85606812 0.84864271 0.33403692 0.78100450 0.46486484 0.77330962
#> [7] 0.71955835 0.43567879 0.28287726 0.38586173 0.71955835 0.36542922
#> [13] 0.34479254 0.44560534 0.20722433 0.78866380 0.15429894 0.49269733
#> [19] 0.51976715 0.38586173 0.62162592 0.89286073 0.81135146 0.69582669
#> [25] 0.98608452 0.18101762 0.46486484 0.51976715 0.11289435 0.87809419
#> [31] 0.27076622 0.85606812 0.95778142 0.92922996 0.49269733 0.80378888
#> [37] 0.57930389 0.36542922 0.28287726 0.28287726 0.11289435 0.97198608
#> [43] 0.11289435 0.25838045 0.03643715 0.64669292 0.97904491 0.98608452
#> [49] 0.91472463 0.88549342 0.66328362 0.92922996 0.71955835 0.22045199
#> [55] 0.51976715 0.07880205 0.90020860 0.63004134 0.40587374 0.15429894
#> [61] 0.92198440 0.60481518 0.65501247 0.74291221 0.18101762 0.67152032
#> [67] 0.82634068 0.57930389 0.60481518 0.96489819 0.23353392 0.42569556
#> [73] 0.51976715 0.74291221 0.23353392 0.78866380 0.34479254 0.74291221
#> [79] 0.69582669 0.46486484 0.51976715 0.56207283 0.85606812 0.81135146
#> [85] 0.67971048 0.94355839 0.90020860 0.84120856 0.40587374 0.69582669
#> [91] 0.82634068 0.44560534 0.94355839 0.07880205 0.28287726 0.03643715
#> [97] 0.57930389 0.56207283 0.28287726 0.67971048 0.74291221 0.63004134
#> [103] 0.49269733 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [109] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [115] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [121] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [127] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [133] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [139] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [145] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [151] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [157] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [163] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [169] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [175] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [181] 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
#> [187] 0.00000000 0.00000000 0.00000000
#>
#> $Time
#> 155 81 90 26 55 100 79 105 36 128 79.1 68 190
#> 13.08 14.06 20.94 15.77 19.34 16.07 16.23 19.75 21.19 20.35 16.23 20.62 20.81
#> 170 63 39 92 76 97 128.1 41 177 133 192 77 113
#> 19.54 22.77 15.59 22.92 19.22 19.14 20.35 18.02 12.53 14.65 16.44 7.27 22.86
#> 58 97.1 69 14 153 155.1 61 159 76.1 167 8 68.1 99
#> 19.34 19.14 23.23 12.89 21.33 13.08 10.12 10.55 19.22 15.55 18.43 20.62 21.19
#> 36.1 69.1 183 69.2 197 168 110 149 77.1 42 140 30 159.1
#> 21.19 23.23 9.24 23.23 21.60 23.72 17.56 8.37 7.27 12.43 12.68 17.43 10.55
#> 79.2 169 97.2 129 37 184 150 92.1 56 51 111 188 113.1
#> 16.23 22.41 19.14 23.41 12.52 17.77 20.33 22.92 12.21 18.23 17.45 16.16 22.86
#> 106 57 8.1 51.1 145 66 166 97.3 188.1 66.1 39.1 190.1 188.2
#> 16.67 14.46 18.43 18.23 10.07 22.13 19.98 19.14 16.16 22.13 15.59 20.81 16.16
#> 192.1 55.1 97.4 179 155.2 133.1 171 93 37.1 13 150.1 192.2 57.1
#> 16.44 19.34 19.14 18.63 13.08 14.65 16.57 10.33 12.52 14.34 20.33 16.44 14.46
#> 170.1 93.1 129.1 99.1 168.1 8.2 179.1 36.2 171.1 188.3 184.1 76.2 46
#> 19.54 10.33 23.41 21.19 23.72 18.43 18.63 21.19 16.57 16.16 17.77 19.22 24.00
#> 75 119 198 142 116 22 122 54 143 31 156 176 138
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 196 94 131 112 83 102 2 156.1 22.1 196.1 17 163 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 94.1 75.1 7 198.1 65 31.1 102.1 71 62 74 144 131.1 22.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 120 64 148 132 35 163.1 28 22.3 64.1 173 9 152 22.4
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 7.1 156.2 3 121 74.1 146 98.1 21 118 21.1 84 193 64.2
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 163.2 132.1 17.1 186 3.1 11 132.2 67 161 34 53 95 87
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 147 132.3 174 148.1 109 87.1 103
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[98]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01224981 0.65942981 0.16598288
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -0.453103274 0.009018644 0.141751865
#> grade_iii, Cure model
#> 0.379118598
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 23 16.92 1 61 0 0
#> 164 23.60 1 76 0 1
#> 117 17.46 1 26 0 1
#> 192 16.44 1 31 1 0
#> 192.1 16.44 1 31 1 0
#> 180 14.82 1 37 0 0
#> 45 17.42 1 54 0 1
#> 14 12.89 1 21 0 0
#> 123 13.00 1 44 1 0
#> 69 23.23 1 25 0 1
#> 187 9.92 1 39 1 0
#> 107 11.18 1 54 1 0
#> 93 10.33 1 52 0 1
#> 60 13.15 1 38 1 0
#> 197 21.60 1 69 1 0
#> 187.1 9.92 1 39 1 0
#> 4 17.64 1 NA 0 1
#> 4.1 17.64 1 NA 0 1
#> 56 12.21 1 60 0 0
#> 117.1 17.46 1 26 0 1
#> 55 19.34 1 69 0 1
#> 60.1 13.15 1 38 1 0
#> 77 7.27 1 67 0 1
#> 197.1 21.60 1 69 1 0
#> 26 15.77 1 49 0 1
#> 105 19.75 1 60 0 0
#> 192.2 16.44 1 31 1 0
#> 18 15.21 1 49 1 0
#> 4.2 17.64 1 NA 0 1
#> 6 15.64 1 39 0 0
#> 153 21.33 1 55 1 0
#> 29 15.45 1 68 1 0
#> 133 14.65 1 57 0 0
#> 113 22.86 1 34 0 0
#> 107.1 11.18 1 54 1 0
#> 43 12.10 1 61 0 1
#> 91 5.33 1 61 0 1
#> 106 16.67 1 49 1 0
#> 25 6.32 1 34 1 0
#> 124 9.73 1 NA 1 0
#> 130 16.47 1 53 0 1
#> 68 20.62 1 44 0 0
#> 70 7.38 1 30 1 0
#> 29.1 15.45 1 68 1 0
#> 57 14.46 1 45 0 1
#> 79 16.23 1 54 1 0
#> 89 11.44 1 NA 0 0
#> 8 18.43 1 32 0 0
#> 100 16.07 1 60 0 0
#> 124.1 9.73 1 NA 1 0
#> 129 23.41 1 53 1 0
#> 4.3 17.64 1 NA 0 1
#> 177 12.53 1 75 0 0
#> 175 21.91 1 43 0 0
#> 66 22.13 1 53 0 0
#> 101 9.97 1 10 0 1
#> 41 18.02 1 40 1 0
#> 192.3 16.44 1 31 1 0
#> 50 10.02 1 NA 1 0
#> 50.1 10.02 1 NA 1 0
#> 149 8.37 1 33 1 0
#> 111 17.45 1 47 0 1
#> 179 18.63 1 42 0 0
#> 166 19.98 1 48 0 0
#> 154 12.63 1 20 1 0
#> 110 17.56 1 65 0 1
#> 195 11.76 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 93.1 10.33 1 52 0 1
#> 168 23.72 1 70 0 0
#> 107.2 11.18 1 54 1 0
#> 42 12.43 1 49 0 1
#> 60.2 13.15 1 38 1 0
#> 49 12.19 1 48 1 0
#> 13 14.34 1 54 0 1
#> 139 21.49 1 63 1 0
#> 86 23.81 1 58 0 1
#> 61 10.12 1 36 0 1
#> 192.4 16.44 1 31 1 0
#> 81 14.06 1 34 0 0
#> 129.1 23.41 1 53 1 0
#> 76 19.22 1 54 0 1
#> 69.1 23.23 1 25 0 1
#> 36 21.19 1 48 0 1
#> 66.1 22.13 1 53 0 0
#> 113.1 22.86 1 34 0 0
#> 24 23.89 1 38 0 0
#> 96 14.54 1 33 0 1
#> 136 21.83 1 43 0 1
#> 14.1 12.89 1 21 0 0
#> 195.1 11.76 1 NA 1 0
#> 26.1 15.77 1 49 0 1
#> 170 19.54 1 43 0 1
#> 49.1 12.19 1 48 1 0
#> 111.1 17.45 1 47 0 1
#> 199 19.81 1 NA 0 1
#> 55.1 19.34 1 69 0 1
#> 58 19.34 1 39 0 0
#> 199.1 19.81 1 NA 0 1
#> 189 10.51 1 NA 1 0
#> 133.1 14.65 1 57 0 0
#> 88 18.37 1 47 0 0
#> 6.1 15.64 1 39 0 0
#> 150 20.33 1 48 0 0
#> 100.1 16.07 1 60 0 0
#> 179.1 18.63 1 42 0 0
#> 184 17.77 1 38 0 0
#> 92 22.92 1 47 0 1
#> 5 16.43 1 51 0 1
#> 76.1 19.22 1 54 0 1
#> 79.1 16.23 1 54 1 0
#> 194 22.40 1 38 0 1
#> 165 24.00 0 47 0 0
#> 46 24.00 0 71 0 0
#> 163 24.00 0 66 0 0
#> 3 24.00 0 31 1 0
#> 151 24.00 0 42 0 0
#> 44 24.00 0 56 0 0
#> 142 24.00 0 53 0 0
#> 95 24.00 0 68 0 1
#> 176 24.00 0 43 0 1
#> 138 24.00 0 44 1 0
#> 115 24.00 0 NA 1 0
#> 138.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 75 24.00 0 21 1 0
#> 144 24.00 0 28 0 1
#> 17 24.00 0 38 0 1
#> 27 24.00 0 63 1 0
#> 109 24.00 0 48 0 0
#> 103 24.00 0 56 1 0
#> 141 24.00 0 44 1 0
#> 35 24.00 0 51 0 0
#> 163.1 24.00 0 66 0 0
#> 174 24.00 0 49 1 0
#> 115.1 24.00 0 NA 1 0
#> 19 24.00 0 57 0 1
#> 9 24.00 0 31 1 0
#> 172 24.00 0 41 0 0
#> 64 24.00 0 43 0 0
#> 182 24.00 0 35 0 0
#> 17.1 24.00 0 38 0 1
#> 2 24.00 0 9 0 0
#> 185 24.00 0 44 1 0
#> 34 24.00 0 36 0 0
#> 141.1 24.00 0 44 1 0
#> 74 24.00 0 43 0 1
#> 53 24.00 0 32 0 1
#> 198 24.00 0 66 0 1
#> 65 24.00 0 57 1 0
#> 178 24.00 0 52 1 0
#> 182.1 24.00 0 35 0 0
#> 82 24.00 0 34 0 0
#> 116 24.00 0 58 0 1
#> 182.2 24.00 0 35 0 0
#> 3.1 24.00 0 31 1 0
#> 191 24.00 0 60 0 1
#> 103.1 24.00 0 56 1 0
#> 152 24.00 0 36 0 1
#> 17.2 24.00 0 38 0 1
#> 95.1 24.00 0 68 0 1
#> 176.1 24.00 0 43 0 1
#> 84 24.00 0 39 0 1
#> 176.2 24.00 0 43 0 1
#> 112 24.00 0 61 0 0
#> 82.1 24.00 0 34 0 0
#> 172.1 24.00 0 41 0 0
#> 132 24.00 0 55 0 0
#> 152.1 24.00 0 36 0 1
#> 160 24.00 0 31 1 0
#> 122 24.00 0 66 0 0
#> 44.1 24.00 0 56 0 0
#> 3.2 24.00 0 31 1 0
#> 64.1 24.00 0 43 0 0
#> 3.3 24.00 0 31 1 0
#> 112.1 24.00 0 61 0 0
#> 132.1 24.00 0 55 0 0
#> 137 24.00 0 45 1 0
#> 11 24.00 0 42 0 1
#> 185.1 24.00 0 44 1 0
#> 75.1 24.00 0 21 1 0
#> 87 24.00 0 27 0 0
#> 121 24.00 0 57 1 0
#> 48 24.00 0 31 1 0
#> 98 24.00 0 34 1 0
#> 103.2 24.00 0 56 1 0
#> 48.1 24.00 0 31 1 0
#> 64.2 24.00 0 43 0 0
#> 19.1 24.00 0 57 0 1
#> 7 24.00 0 37 1 0
#> 142.1 24.00 0 53 0 0
#> 47 24.00 0 38 0 1
#> 146 24.00 0 63 1 0
#> 151.1 24.00 0 42 0 0
#> 20 24.00 0 46 1 0
#> 19.2 24.00 0 57 0 1
#> 27.1 24.00 0 63 1 0
#> 144.1 24.00 0 28 0 1
#> 53.1 24.00 0 32 0 1
#> 71 24.00 0 51 0 0
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -0.453 NA NA NA
#> 2 age, Cure model 0.00902 NA NA NA
#> 3 grade_ii, Cure model 0.142 NA NA NA
#> 4 grade_iii, Cure model 0.379 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0122 NA NA NA
#> 2 grade_ii, Survival model 0.659 NA NA NA
#> 3 grade_iii, Survival model 0.166 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.453103 0.009019 0.141752 0.379119
#>
#> Degrees of Freedom: 183 Total (i.e. Null); 180 Residual
#> Null Deviance: 254.3
#> Residual Deviance: 252.6 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -0.453103274 0.009018644 0.141751865 0.379118598
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01224981 0.65942981 0.16598288
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.3385666051 0.0090944903 0.2836014879 0.3733985174 0.3733985174
#> [6] 0.5753158144 0.3271929447 0.7099606214 0.6976151043 0.0238097857
#> [11] 0.9109494499 0.8222810753 0.8597685165 0.6611490056 0.0842679723
#> [16] 0.9109494499 0.7719478267 0.2836014879 0.1641809737 0.6611490056
#> [21] 0.9617504757 0.0842679723 0.4816589972 0.1465678227 0.3733985174
#> [26] 0.5634218549 0.5046389229 0.1064124676 0.5398550274 0.5873000724
#> [31] 0.0390555223 0.8222810753 0.8095917187 0.9872170421 0.3501450032
#> [36] 0.9745066333 0.3617001393 0.1218389301 0.9490750892 0.5398550274
#> [41] 0.6237978769 0.4370237783 0.2306087468 0.4590590183 0.0146497566
#> [46] 0.7469627151 0.0697189593 0.0566378078 0.8980915257 0.2515772056
#> [51] 0.3733985174 0.9363420542 0.3051353340 0.2105932229 0.1380995393
#> [56] 0.7346299550 0.2727413677 0.5280234212 0.8597685165 0.0049282876
#> [61] 0.8222810753 0.7594190748 0.6611490056 0.7845833199 0.6361578802
#> [66] 0.0987970762 0.0021536099 0.8852254180 0.3733985174 0.6486124395
#> [71] 0.0146497566 0.1913154100 0.0238097857 0.1140358405 0.0566378078
#> [76] 0.0390555223 0.0004379487 0.6115156875 0.0768890897 0.7099606214
#> [81] 0.4816589972 0.1552987352 0.7845833199 0.3051353340 0.1641809737
#> [86] 0.1641809737 0.5873000724 0.2409931429 0.5046389229 0.1298560617
#> [91] 0.4590590183 0.2105932229 0.2620797623 0.0335022187 0.4258649560
#> [96] 0.1913154100 0.4370237783 0.0504067997 0.0000000000 0.0000000000
#> [101] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [106] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#>
#> $Time
#> 23 164 117 192 192.1 180 45 14 123 69 187 107 93
#> 16.92 23.60 17.46 16.44 16.44 14.82 17.42 12.89 13.00 23.23 9.92 11.18 10.33
#> 60 197 187.1 56 117.1 55 60.1 77 197.1 26 105 192.2 18
#> 13.15 21.60 9.92 12.21 17.46 19.34 13.15 7.27 21.60 15.77 19.75 16.44 15.21
#> 6 153 29 133 113 107.1 43 91 106 25 130 68 70
#> 15.64 21.33 15.45 14.65 22.86 11.18 12.10 5.33 16.67 6.32 16.47 20.62 7.38
#> 29.1 57 79 8 100 129 177 175 66 101 41 192.3 149
#> 15.45 14.46 16.23 18.43 16.07 23.41 12.53 21.91 22.13 9.97 18.02 16.44 8.37
#> 111 179 166 154 110 167 93.1 168 107.2 42 60.2 49 13
#> 17.45 18.63 19.98 12.63 17.56 15.55 10.33 23.72 11.18 12.43 13.15 12.19 14.34
#> 139 86 61 192.4 81 129.1 76 69.1 36 66.1 113.1 24 96
#> 21.49 23.81 10.12 16.44 14.06 23.41 19.22 23.23 21.19 22.13 22.86 23.89 14.54
#> 136 14.1 26.1 170 49.1 111.1 55.1 58 133.1 88 6.1 150 100.1
#> 21.83 12.89 15.77 19.54 12.19 17.45 19.34 19.34 14.65 18.37 15.64 20.33 16.07
#> 179.1 184 92 5 76.1 79.1 194 165 46 163 3 151 44
#> 18.63 17.77 22.92 16.43 19.22 16.23 22.40 24.00 24.00 24.00 24.00 24.00 24.00
#> 142 95 176 138 138.1 135 75 144 17 27 109 103 141
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 35 163.1 174 19 9 172 64 182 17.1 2 185 34 141.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 74 53 198 65 178 182.1 82 116 182.2 3.1 191 103.1 152
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17.2 95.1 176.1 84 176.2 112 82.1 172.1 132 152.1 160 122 44.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 3.2 64.1 3.3 112.1 132.1 137 11 185.1 75.1 87 121 48 98
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 103.2 48.1 64.2 19.1 7 142.1 47 146 151.1 20 19.2 27.1 144.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 53.1 71
#> 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[99]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01601888 0.42744662 0.52524324
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> 0.133143010 -0.002248185 -0.020733596
#> grade_iii, Cure model
#> 0.666773718
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 180 14.82 1 37 0 0
#> 91 5.33 1 61 0 1
#> 41 18.02 1 40 1 0
#> 124 9.73 1 NA 1 0
#> 52 10.42 1 52 0 1
#> 57 14.46 1 45 0 1
#> 123 13.00 1 44 1 0
#> 37 12.52 1 57 1 0
#> 117 17.46 1 26 0 1
#> 155 13.08 1 26 0 0
#> 158 20.14 1 74 1 0
#> 92 22.92 1 47 0 1
#> 59 10.16 1 NA 1 0
#> 194 22.40 1 38 0 1
#> 101 9.97 1 10 0 1
#> 170 19.54 1 43 0 1
#> 8 18.43 1 32 0 0
#> 76 19.22 1 54 0 1
#> 125 15.65 1 67 1 0
#> 81 14.06 1 34 0 0
#> 184 17.77 1 38 0 0
#> 93 10.33 1 52 0 1
#> 78 23.88 1 43 0 0
#> 58 19.34 1 39 0 0
#> 188 16.16 1 46 0 1
#> 187 9.92 1 39 1 0
#> 78.1 23.88 1 43 0 0
#> 197 21.60 1 69 1 0
#> 155.1 13.08 1 26 0 0
#> 42 12.43 1 49 0 1
#> 130 16.47 1 53 0 1
#> 91.1 5.33 1 61 0 1
#> 50 10.02 1 NA 1 0
#> 136 21.83 1 43 0 1
#> 68 20.62 1 44 0 0
#> 199 19.81 1 NA 0 1
#> 158.1 20.14 1 74 1 0
#> 60 13.15 1 38 1 0
#> 190 20.81 1 42 1 0
#> 166 19.98 1 48 0 0
#> 130.1 16.47 1 53 0 1
#> 113 22.86 1 34 0 0
#> 18 15.21 1 49 1 0
#> 153 21.33 1 55 1 0
#> 155.2 13.08 1 26 0 0
#> 187.1 9.92 1 39 1 0
#> 40 18.00 1 28 1 0
#> 14 12.89 1 21 0 0
#> 188.1 16.16 1 46 0 1
#> 25 6.32 1 34 1 0
#> 45 17.42 1 54 0 1
#> 97 19.14 1 65 0 1
#> 171 16.57 1 41 0 1
#> 166.1 19.98 1 48 0 0
#> 85 16.44 1 36 0 0
#> 57.1 14.46 1 45 0 1
#> 105 19.75 1 60 0 0
#> 155.3 13.08 1 26 0 0
#> 23 16.92 1 61 0 0
#> 43 12.10 1 61 0 1
#> 77 7.27 1 67 0 1
#> 164 23.60 1 76 0 1
#> 10 10.53 1 34 0 0
#> 61 10.12 1 36 0 1
#> 134 17.81 1 47 1 0
#> 133 14.65 1 57 0 0
#> 5 16.43 1 51 0 1
#> 91.2 5.33 1 61 0 1
#> 50.1 10.02 1 NA 1 0
#> 40.1 18.00 1 28 1 0
#> 106 16.67 1 49 1 0
#> 158.2 20.14 1 74 1 0
#> 86 23.81 1 58 0 1
#> 96 14.54 1 33 0 1
#> 52.1 10.42 1 52 0 1
#> 100 16.07 1 60 0 0
#> 43.1 12.10 1 61 0 1
#> 128 20.35 1 35 0 1
#> 108 18.29 1 39 0 1
#> 166.2 19.98 1 48 0 0
#> 57.2 14.46 1 45 0 1
#> 26 15.77 1 49 0 1
#> 184.1 17.77 1 38 0 0
#> 96.1 14.54 1 33 0 1
#> 145 10.07 1 65 1 0
#> 101.1 9.97 1 10 0 1
#> 134.1 17.81 1 47 1 0
#> 190.1 20.81 1 42 1 0
#> 15 22.68 1 48 0 0
#> 197.1 21.60 1 69 1 0
#> 111 17.45 1 47 0 1
#> 159 10.55 1 50 0 1
#> 166.3 19.98 1 48 0 0
#> 100.1 16.07 1 60 0 0
#> 113.1 22.86 1 34 0 0
#> 125.1 15.65 1 67 1 0
#> 177 12.53 1 75 0 0
#> 139 21.49 1 63 1 0
#> 168 23.72 1 70 0 0
#> 158.3 20.14 1 74 1 0
#> 26.1 15.77 1 49 0 1
#> 13 14.34 1 54 0 1
#> 5.1 16.43 1 51 0 1
#> 107 11.18 1 54 1 0
#> 40.2 18.00 1 28 1 0
#> 194.1 22.40 1 38 0 1
#> 70 7.38 1 30 1 0
#> 129 23.41 1 53 1 0
#> 23.1 16.92 1 61 0 0
#> 183 9.24 1 67 1 0
#> 61.1 10.12 1 36 0 1
#> 14.1 12.89 1 21 0 0
#> 143 24.00 0 51 0 0
#> 83 24.00 0 6 0 0
#> 165 24.00 0 47 0 0
#> 62 24.00 0 71 0 0
#> 44 24.00 0 56 0 0
#> 118 24.00 0 44 1 0
#> 200 24.00 0 64 0 0
#> 196 24.00 0 19 0 0
#> 156 24.00 0 50 1 0
#> 122 24.00 0 66 0 0
#> 182 24.00 0 35 0 0
#> 176 24.00 0 43 0 1
#> 120 24.00 0 68 0 1
#> 65 24.00 0 57 1 0
#> 11 24.00 0 42 0 1
#> 120.1 24.00 0 68 0 1
#> 115 24.00 0 NA 1 0
#> 11.1 24.00 0 42 0 1
#> 120.2 24.00 0 68 0 1
#> 11.2 24.00 0 42 0 1
#> 87 24.00 0 27 0 0
#> 11.3 24.00 0 42 0 1
#> 84 24.00 0 39 0 1
#> 109 24.00 0 48 0 0
#> 9 24.00 0 31 1 0
#> 137 24.00 0 45 1 0
#> 156.1 24.00 0 50 1 0
#> 75 24.00 0 21 1 0
#> 191 24.00 0 60 0 1
#> 141 24.00 0 44 1 0
#> 82 24.00 0 34 0 0
#> 120.3 24.00 0 68 0 1
#> 174 24.00 0 49 1 0
#> 115.1 24.00 0 NA 1 0
#> 103 24.00 0 56 1 0
#> 141.1 24.00 0 44 1 0
#> 135 24.00 0 58 1 0
#> 196.1 24.00 0 19 0 0
#> 82.1 24.00 0 34 0 0
#> 118.1 24.00 0 44 1 0
#> 174.1 24.00 0 49 1 0
#> 84.1 24.00 0 39 0 1
#> 143.1 24.00 0 51 0 0
#> 178 24.00 0 52 1 0
#> 161 24.00 0 45 0 0
#> 109.1 24.00 0 48 0 0
#> 72 24.00 0 40 0 1
#> 109.2 24.00 0 48 0 0
#> 31 24.00 0 36 0 1
#> 3 24.00 0 31 1 0
#> 95 24.00 0 68 0 1
#> 12 24.00 0 63 0 0
#> 62.1 24.00 0 71 0 0
#> 146 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 22 24.00 0 52 1 0
#> 94 24.00 0 51 0 1
#> 64 24.00 0 43 0 0
#> 83.1 24.00 0 6 0 0
#> 65.1 24.00 0 57 1 0
#> 65.2 24.00 0 57 1 0
#> 135.1 24.00 0 58 1 0
#> 173 24.00 0 19 0 1
#> 115.2 24.00 0 NA 1 0
#> 148.1 24.00 0 61 1 0
#> 46 24.00 0 71 0 0
#> 132 24.00 0 55 0 0
#> 47 24.00 0 38 0 1
#> 31.1 24.00 0 36 0 1
#> 94.1 24.00 0 51 0 1
#> 67 24.00 0 25 0 0
#> 198 24.00 0 66 0 1
#> 174.2 24.00 0 49 1 0
#> 54 24.00 0 53 1 0
#> 65.3 24.00 0 57 1 0
#> 122.1 24.00 0 66 0 0
#> 146.1 24.00 0 63 1 0
#> 35 24.00 0 51 0 0
#> 73 24.00 0 NA 0 1
#> 46.1 24.00 0 71 0 0
#> 9.1 24.00 0 31 1 0
#> 186 24.00 0 45 1 0
#> 48 24.00 0 31 1 0
#> 200.1 24.00 0 64 0 0
#> 165.1 24.00 0 47 0 0
#> 12.1 24.00 0 63 0 0
#> 3.1 24.00 0 31 1 0
#> 144 24.00 0 28 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model 0.133 NA NA NA
#> 2 age, Cure model -0.00225 NA NA NA
#> 3 grade_ii, Cure model -0.0207 NA NA NA
#> 4 grade_iii, Cure model 0.667 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0160 NA NA NA
#> 2 grade_ii, Survival model 0.427 NA NA NA
#> 3 grade_iii, Survival model 0.525 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.133143 -0.002248 -0.020734 0.666774
#>
#> Degrees of Freedom: 190 Total (i.e. Null); 187 Residual
#> Null Deviance: 262
#> Residual Deviance: 257.2 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> 0.133143010 -0.002248185 -0.020733596 0.666773718
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01601888 0.42744662 0.52524324
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.4775250709 0.9600270217 0.1944602708 0.7768224192 0.5229329494
#> [6] 0.6390746239 0.6879418966 0.2643200689 0.5920976044 0.0831355495
#> [11] 0.0118602123 0.0270315789 0.8551018484 0.1439819272 0.1770661692
#> [16] 0.1602151530 0.4444108096 0.5685732838 0.2461510361 0.8027175783
#> [21] 0.0002634221 0.1519978444 0.3812760723 0.8809927136 0.0002634221
#> [26] 0.0399556629 0.5920976044 0.7004511796 0.3310442421 0.9600270217
#> [31] 0.0354015254 0.0712780818 0.0831355495 0.5803156783 0.0603672991
#> [36] 0.1078442925 0.3310442421 0.0152762525 0.4663456021 0.0548698840
#> [41] 0.5920976044 0.8809927136 0.2032523943 0.6512128350 0.3812760723
#> [46] 0.9467177925 0.2828021833 0.1685557612 0.3211736676 0.1078442925
#> [51] 0.3508125075 0.5229329494 0.1360328833 0.5920976044 0.2921634760
#> [56] 0.7130117695 0.9334292255 0.0057887825 0.7638803877 0.8158277748
#> [61] 0.2285738725 0.4888228196 0.3609671624 0.9600270217 0.2032523943
#> [66] 0.3113403600 0.0831355495 0.0019296734 0.5002790998 0.7768224192
#> [71] 0.4017936413 0.7130117695 0.0771987854 0.1857439038 0.1078442925
#> [76] 0.5229329494 0.4229793889 0.2461510361 0.5002790998 0.8418791972
#> [81] 0.8551018484 0.2285738725 0.0603672991 0.0225924643 0.0399556629
#> [86] 0.2735293334 0.7510297912 0.1078442925 0.4017936413 0.0152762525
#> [91] 0.4444108096 0.6755195129 0.0495665015 0.0035092613 0.0831355495
#> [96] 0.4229793889 0.5569318600 0.3609671624 0.7382319641 0.2032523943
#> [101] 0.0270315789 0.9202200003 0.0086380415 0.2921634760 0.9070205802
#> [106] 0.8158277748 0.6512128350 0.0000000000 0.0000000000 0.0000000000
#> [111] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [116] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [121] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [126] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [131] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [136] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [141] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [146] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [151] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [156] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [161] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [166] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [171] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [176] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [181] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [186] 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
#> [191] 0.0000000000
#>
#> $Time
#> 180 91 41 52 57 123 37 117 155 158 92 194 101
#> 14.82 5.33 18.02 10.42 14.46 13.00 12.52 17.46 13.08 20.14 22.92 22.40 9.97
#> 170 8 76 125 81 184 93 78 58 188 187 78.1 197
#> 19.54 18.43 19.22 15.65 14.06 17.77 10.33 23.88 19.34 16.16 9.92 23.88 21.60
#> 155.1 42 130 91.1 136 68 158.1 60 190 166 130.1 113 18
#> 13.08 12.43 16.47 5.33 21.83 20.62 20.14 13.15 20.81 19.98 16.47 22.86 15.21
#> 153 155.2 187.1 40 14 188.1 25 45 97 171 166.1 85 57.1
#> 21.33 13.08 9.92 18.00 12.89 16.16 6.32 17.42 19.14 16.57 19.98 16.44 14.46
#> 105 155.3 23 43 77 164 10 61 134 133 5 91.2 40.1
#> 19.75 13.08 16.92 12.10 7.27 23.60 10.53 10.12 17.81 14.65 16.43 5.33 18.00
#> 106 158.2 86 96 52.1 100 43.1 128 108 166.2 57.2 26 184.1
#> 16.67 20.14 23.81 14.54 10.42 16.07 12.10 20.35 18.29 19.98 14.46 15.77 17.77
#> 96.1 145 101.1 134.1 190.1 15 197.1 111 159 166.3 100.1 113.1 125.1
#> 14.54 10.07 9.97 17.81 20.81 22.68 21.60 17.45 10.55 19.98 16.07 22.86 15.65
#> 177 139 168 158.3 26.1 13 5.1 107 40.2 194.1 70 129 23.1
#> 12.53 21.49 23.72 20.14 15.77 14.34 16.43 11.18 18.00 22.40 7.38 23.41 16.92
#> 183 61.1 14.1 143 83 165 62 44 118 200 196 156 122
#> 9.24 10.12 12.89 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 182 176 120 65 11 120.1 11.1 120.2 11.2 87 11.3 84 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 9 137 156.1 75 191 141 82 120.3 174 103 141.1 135 196.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 82.1 118.1 174.1 84.1 143.1 178 161 109.1 72 109.2 31 3 95
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 12 62.1 146 148 22 94 64 83.1 65.1 65.2 135.1 173 148.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46 132 47 31.1 94.1 67 198 174.2 54 65.3 122.1 146.1 35
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 46.1 9.1 186 48 200.1 165.1 12.1 3.1 144
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#> $bootstrap_fit[[100]]
#> <cureit>
#> $surv_coefs
#> age, Survival model grade_ii, Survival model grade_iii, Survival model
#> -0.01257149 0.82890246 0.60355964
#>
#> $cure_coefs
#> (Intercept), Cure model age, Cure model grade_ii, Cure model
#> -1.24096755 0.03098944 -0.23254808
#> grade_iii, Cure model
#> 0.07280401
#>
#> $surv_formula
#> Surv(time, status) ~ age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $cure_formula
#> ~age + grade_ii + grade_iii
#> <environment: 0x55a857a1a2f8>
#>
#> $data
#> time status age grade_ii grade_iii
#> 63 22.77 1 31 1 0
#> 181 16.46 1 45 0 1
#> 177 12.53 1 75 0 0
#> 78 23.88 1 43 0 0
#> 23 16.92 1 61 0 0
#> 158 20.14 1 74 1 0
#> 197 21.60 1 69 1 0
#> 32 20.90 1 37 1 0
#> 169 22.41 1 46 0 0
#> 76 19.22 1 54 0 1
#> 159 10.55 1 50 0 1
#> 81 14.06 1 34 0 0
#> 15 22.68 1 48 0 0
#> 125 15.65 1 67 1 0
#> 60 13.15 1 38 1 0
#> 150 20.33 1 48 0 0
#> 107 11.18 1 54 1 0
#> 189 10.51 1 NA 1 0
#> 167 15.55 1 56 1 0
#> 85 16.44 1 36 0 0
#> 183 9.24 1 67 1 0
#> 55 19.34 1 69 0 1
#> 39 15.59 1 37 0 1
#> 127 3.53 1 62 0 1
#> 124 9.73 1 NA 1 0
#> 30 17.43 1 78 0 0
#> 149 8.37 1 33 1 0
#> 133 14.65 1 57 0 0
#> 187 9.92 1 39 1 0
#> 25 6.32 1 34 1 0
#> 18 15.21 1 49 1 0
#> 180 14.82 1 37 0 0
#> 169.1 22.41 1 46 0 0
#> 70 7.38 1 30 1 0
#> 14 12.89 1 21 0 0
#> 29 15.45 1 68 1 0
#> 140 12.68 1 59 1 0
#> 199 19.81 1 NA 0 1
#> 100 16.07 1 60 0 0
#> 125.1 15.65 1 67 1 0
#> 23.1 16.92 1 61 0 0
#> 123 13.00 1 44 1 0
#> 91 5.33 1 61 0 1
#> 10 10.53 1 34 0 0
#> 26 15.77 1 49 0 1
#> 154 12.63 1 20 1 0
#> 139 21.49 1 63 1 0
#> 61 10.12 1 36 0 1
#> 68 20.62 1 44 0 0
#> 153 21.33 1 55 1 0
#> 76.1 19.22 1 54 0 1
#> 108 18.29 1 39 0 1
#> 90 20.94 1 50 0 1
#> 68.1 20.62 1 44 0 0
#> 184 17.77 1 38 0 0
#> 158.1 20.14 1 74 1 0
#> 23.2 16.92 1 61 0 0
#> 140.1 12.68 1 59 1 0
#> 89 11.44 1 NA 0 0
#> 195 11.76 1 NA 1 0
#> 4 17.64 1 NA 0 1
#> 124.1 9.73 1 NA 1 0
#> 57 14.46 1 45 0 1
#> 26.1 15.77 1 49 0 1
#> 177.1 12.53 1 75 0 0
#> 155 13.08 1 26 0 0
#> 43 12.10 1 61 0 1
#> 168 23.72 1 70 0 0
#> 42 12.43 1 49 0 1
#> 123.1 13.00 1 44 1 0
#> 183.1 9.24 1 67 1 0
#> 181.1 16.46 1 45 0 1
#> 168.1 23.72 1 70 0 0
#> 127.1 3.53 1 62 0 1
#> 8 18.43 1 32 0 0
#> 57.1 14.46 1 45 0 1
#> 169.2 22.41 1 46 0 0
#> 164 23.60 1 76 0 1
#> 36 21.19 1 48 0 1
#> 175 21.91 1 43 0 0
#> 78.1 23.88 1 43 0 0
#> 187.1 9.92 1 39 1 0
#> 58 19.34 1 39 0 0
#> 25.1 6.32 1 34 1 0
#> 130 16.47 1 53 0 1
#> 128 20.35 1 35 0 1
#> 51 18.23 1 83 0 1
#> 187.2 9.92 1 39 1 0
#> 194 22.40 1 38 0 1
#> 106 16.67 1 49 1 0
#> 37 12.52 1 57 1 0
#> 157 15.10 1 47 0 0
#> 188 16.16 1 46 0 1
#> 58.1 19.34 1 39 0 0
#> 168.2 23.72 1 70 0 0
#> 168.3 23.72 1 70 0 0
#> 39.1 15.59 1 37 0 1
#> 110 17.56 1 65 0 1
#> 195.1 11.76 1 NA 1 0
#> 105 19.75 1 60 0 0
#> 61.1 10.12 1 36 0 1
#> 26.2 15.77 1 49 0 1
#> 36.1 21.19 1 48 0 1
#> 177.2 12.53 1 75 0 0
#> 100.1 16.07 1 60 0 0
#> 192 16.44 1 31 1 0
#> 199.1 19.81 1 NA 0 1
#> 88 18.37 1 47 0 0
#> 99 21.19 1 38 0 1
#> 129 23.41 1 53 1 0
#> 45 17.42 1 54 0 1
#> 6 15.64 1 39 0 0
#> 27 24.00 0 63 1 0
#> 64 24.00 0 43 0 0
#> 21 24.00 0 47 0 0
#> 38 24.00 0 31 1 0
#> 196 24.00 0 19 0 0
#> 87 24.00 0 27 0 0
#> 104 24.00 0 50 1 0
#> 156 24.00 0 50 1 0
#> 120 24.00 0 68 0 1
#> 33 24.00 0 53 0 0
#> 186 24.00 0 45 1 0
#> 162 24.00 0 51 0 0
#> 87.1 24.00 0 27 0 0
#> 46 24.00 0 71 0 0
#> 121 24.00 0 57 1 0
#> 160 24.00 0 31 1 0
#> 75 24.00 0 21 1 0
#> 75.1 24.00 0 21 1 0
#> 152 24.00 0 36 0 1
#> 165 24.00 0 47 0 0
#> 121.1 24.00 0 57 1 0
#> 173 24.00 0 19 0 1
#> 146 24.00 0 63 1 0
#> 138 24.00 0 44 1 0
#> 144 24.00 0 28 0 1
#> 80 24.00 0 41 0 0
#> 67 24.00 0 25 0 0
#> 118 24.00 0 44 1 0
#> 44 24.00 0 56 0 0
#> 196.1 24.00 0 19 0 0
#> 3 24.00 0 31 1 0
#> 182 24.00 0 35 0 0
#> 200 24.00 0 64 0 0
#> 31 24.00 0 36 0 1
#> 193 24.00 0 45 0 1
#> 31.1 24.00 0 36 0 1
#> 71 24.00 0 51 0 0
#> 161 24.00 0 45 0 0
#> 3.1 24.00 0 31 1 0
#> 109 24.00 0 48 0 0
#> 138.1 24.00 0 44 1 0
#> 185 24.00 0 44 1 0
#> 185.1 24.00 0 44 1 0
#> 2 24.00 0 9 0 0
#> 142 24.00 0 53 0 0
#> 144.1 24.00 0 28 0 1
#> 191 24.00 0 60 0 1
#> 33.1 24.00 0 53 0 0
#> 74 24.00 0 43 0 1
#> 72 24.00 0 40 0 1
#> 27.1 24.00 0 63 1 0
#> 148 24.00 0 61 1 0
#> 116 24.00 0 58 0 1
#> 160.1 24.00 0 31 1 0
#> 126 24.00 0 48 0 0
#> 7 24.00 0 37 1 0
#> 122 24.00 0 66 0 0
#> 22 24.00 0 52 1 0
#> 95 24.00 0 68 0 1
#> 47 24.00 0 38 0 1
#> 191.1 24.00 0 60 0 1
#> 35 24.00 0 51 0 0
#> 47.1 24.00 0 38 0 1
#> 53 24.00 0 32 0 1
#> 11 24.00 0 42 0 1
#> 48 24.00 0 31 1 0
#> 193.1 24.00 0 45 0 1
#> 176 24.00 0 43 0 1
#> 73 24.00 0 NA 0 1
#> 141 24.00 0 44 1 0
#> 161.1 24.00 0 45 0 0
#> 148.1 24.00 0 61 1 0
#> 122.1 24.00 0 66 0 0
#> 27.2 24.00 0 63 1 0
#> 103 24.00 0 56 1 0
#> 103.1 24.00 0 56 1 0
#> 143 24.00 0 51 0 0
#> 84 24.00 0 39 0 1
#> 12 24.00 0 63 0 0
#> 186.1 24.00 0 45 1 0
#> 17 24.00 0 38 0 1
#> 75.2 24.00 0 21 1 0
#> 19 24.00 0 57 0 1
#> 104.1 24.00 0 50 1 0
#> 83 24.00 0 6 0 0
#> 12.1 24.00 0 63 0 0
#> 193.2 24.00 0 45 0 1
#> 173.1 24.00 0 19 0 1
#>
#> $conf.level
#> [1] 0.95
#>
#> $nboot
#> [1] 100
#>
#> $eps
#> [1] 1e-07
#>
#> $surv_xlevels
#> named list()
#>
#> $cure_xlevels
#> named list()
#>
#> $tidy
#> $tidy$df_cure
#> # A tibble: 4 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 (Intercept), Cure model -1.24 NA NA NA
#> 2 age, Cure model 0.0310 NA NA NA
#> 3 grade_ii, Cure model -0.233 NA NA NA
#> 4 grade_iii, Cure model 0.0728 NA NA NA
#>
#> $tidy$df_surv
#> # A tibble: 3 × 5
#> term estimate std.error statistic p.value
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 age, Survival model -0.0126 NA NA NA
#> 2 grade_ii, Survival model 0.829 NA NA NA
#> 3 grade_iii, Survival model 0.604 NA NA NA
#>
#>
#> $smcure
#> $logistfit
#>
#> Call: glm(formula = w ~ Z[, -1], family = quasibinomial(link = "logit"))
#>
#> Coefficients:
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.24097 0.03099 -0.23255 0.07280
#>
#> Degrees of Freedom: 189 Total (i.e. Null); 186 Residual
#> Null Deviance: 262
#> Residual Deviance: 252.5 AIC: NA
#>
#> $b
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> -1.24096755 0.03098944 -0.23254808 0.07280401
#>
#> $beta
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> -0.01257149 0.82890246 0.60355964
#>
#> $b_var
#> [1] NA NA NA NA
#>
#> $b_sd
#> [1] NA NA NA NA
#>
#> $b_zvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $b_pvalue
#> (Intercept) Z[, -1]age Z[, -1]grade_ii Z[, -1]grade_iii
#> NA NA NA NA
#>
#> $beta_var
#> [1] NA NA NA
#>
#> $beta_sd
#> [1] NA NA NA
#>
#> $beta_zvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $beta_pvalue
#> X[, -1]age X[, -1]grade_ii X[, -1]grade_iii
#> NA NA NA
#>
#> $call
#> .f(formula = ..1, cureform = ..2, data = ..3, model = "ph", eps = ..6,
#> nboot = 1)
#>
#> $bnm
#> [1] "(Intercept)" "age" "grade_ii" "grade_iii"
#>
#> $betanm
#> [1] "age" "grade_ii" "grade_iii"
#>
#> $s
#> [1] 0.040186148 0.402912512 0.748831372 0.001066076 0.350212811 0.197832505
#> [7] 0.095197533 0.154731581 0.054619731 0.251897074 0.826282928 0.650179187
#> [13] 0.047152433 0.508878321 0.661292139 0.188951388 0.815162193 0.562849508
#> [19] 0.423968914 0.903153839 0.224488236 0.541312127 0.978618372 0.329705055
#> [25] 0.924932380 0.617206768 0.870694147 0.946636512 0.584546487 0.606241761
#> [31] 0.054619731 0.935820377 0.705181900 0.573695366 0.716191547 0.455527493
#> [37] 0.508878321 0.350212811 0.683412740 0.967906479 0.837407365 0.477003122
#> [43] 0.737981091 0.104118649 0.848583442 0.163140305 0.113011608 0.251897074
#> [49] 0.290051877 0.146117654 0.163140305 0.309670283 0.197832505 0.350212811
#> [55] 0.716191547 0.628272345 0.477003122 0.748831372 0.672327073 0.804016846
#> [61] 0.005935652 0.792894730 0.683412740 0.903153839 0.402912512 0.005935652
#> [67] 0.978618372 0.270619104 0.628272345 0.054619731 0.024469602 0.121803024
#> [73] 0.086308489 0.001066076 0.870694147 0.224488236 0.946636512 0.392221335
#> [79] 0.180255492 0.299803963 0.870694147 0.077786395 0.381547864 0.781774546
#> [85] 0.595350033 0.444927996 0.224488236 0.005935652 0.005935652 0.541312127
#> [91] 0.319657473 0.215345148 0.848583442 0.477003122 0.121803024 0.748831372
#> [97] 0.455527493 0.423968914 0.280260341 0.121803024 0.032490019 0.339947705
#> [103] 0.530368905 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [109] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [115] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [121] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [127] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [133] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [139] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [145] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [151] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [157] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [163] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [169] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [175] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [181] 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000 0.000000000
#> [187] 0.000000000 0.000000000 0.000000000 0.000000000
#>
#> $Time
#> 63 181 177 78 23 158 197 32 169 76 159 81 15
#> 22.77 16.46 12.53 23.88 16.92 20.14 21.60 20.90 22.41 19.22 10.55 14.06 22.68
#> 125 60 150 107 167 85 183 55 39 127 30 149 133
#> 15.65 13.15 20.33 11.18 15.55 16.44 9.24 19.34 15.59 3.53 17.43 8.37 14.65
#> 187 25 18 180 169.1 70 14 29 140 100 125.1 23.1 123
#> 9.92 6.32 15.21 14.82 22.41 7.38 12.89 15.45 12.68 16.07 15.65 16.92 13.00
#> 91 10 26 154 139 61 68 153 76.1 108 90 68.1 184
#> 5.33 10.53 15.77 12.63 21.49 10.12 20.62 21.33 19.22 18.29 20.94 20.62 17.77
#> 158.1 23.2 140.1 57 26.1 177.1 155 43 168 42 123.1 183.1 181.1
#> 20.14 16.92 12.68 14.46 15.77 12.53 13.08 12.10 23.72 12.43 13.00 9.24 16.46
#> 168.1 127.1 8 57.1 169.2 164 36 175 78.1 187.1 58 25.1 130
#> 23.72 3.53 18.43 14.46 22.41 23.60 21.19 21.91 23.88 9.92 19.34 6.32 16.47
#> 128 51 187.2 194 106 37 157 188 58.1 168.2 168.3 39.1 110
#> 20.35 18.23 9.92 22.40 16.67 12.52 15.10 16.16 19.34 23.72 23.72 15.59 17.56
#> 105 61.1 26.2 36.1 177.2 100.1 192 88 99 129 45 6 27
#> 19.75 10.12 15.77 21.19 12.53 16.07 16.44 18.37 21.19 23.41 17.42 15.64 24.00
#> 64 21 38 196 87 104 156 120 33 186 162 87.1 46
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 121 160 75 75.1 152 165 121.1 173 146 138 144 80 67
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 118 44 196.1 3 182 200 31 193 31.1 71 161 3.1 109
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 138.1 185 185.1 2 142 144.1 191 33.1 74 72 27.1 148 116
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 160.1 126 7 122 22 95 47 191.1 35 47.1 53 11 48
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 193.1 176 141 161.1 148.1 122.1 27.2 103 103.1 143 84 12 186.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#> 17 75.2 19 104.1 83 12.1 193.2 173.1
#> 24.00 24.00 24.00 24.00 24.00 24.00 24.00 24.00
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> NULL
#>
#> $cure_blueprint
#> NULL
#>
#>
#>
#> attr(,"class")
#> [1] "smcure"
#>
#> $surv_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 2
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>
#> $cure_blueprint
#> Formula blueprint:
#>
#> # Predictors: 2
#> # Outcomes: 0
#> Intercept: TRUE
#> Novel Levels: FALSE
#> Composition: tibble
#> Indicators: traditional
#>